{"as_of":"2026-08-17T22:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2754b3cfeefb7b3fb2b176c3e39574a0b4debd5688cbd930fffccfdc93f0d332","coverage":[{"denominator":99,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":99,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T04:44:40.927495Z","state":"measured"},{"denominator":99,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":99,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.18489/citation-record","integrity":"/paper/2412.18489/integrity","json":"/paper/2412.18489/citation-record.json","paper":"/paper/2412.18489"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.483142Z","title":"Applications of diaLogic System in Individual and Team-based Problem Solving Applications","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.483142Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:85604b6d9f31f5596754ea9acc54e1c2dd12fc2b6679efed8a4dee2c4ed6e461","observation_id":"37f19942-536e-4d43-80d2-1b6efca560e6","resolution":{"observed_at":"2026-08-11T04:44:40.483142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.488791Z","title":"Using Speech Data to Automatically Charac- terize Team Effectiveness to Optimize Power Distribution in Internet- of-Things Applications","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.488791Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:efbbd537c1f139f359da60623f08b6b7db02b29ddbdde8986afc5373a4bbaec8","observation_id":"337ddcd6-9da4-4c81-b600-1218316a13ed","resolution":{"observed_at":"2026-08-11T04:44:40.488791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.493833Z","title":"Studying Consensus and Disagreement during Problem Solving in Teams through Learning and Response Generation Agents Model","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.493833Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:8bf0cfbecdd3c0291539f907da8a0fc97423ea5a097d01d40a77b2656ea1f525","observation_id":"6ac12a7f-5304-4eab-be7b-c1f89c3a4ade","resolution":{"observed_at":"2026-08-11T04:44:40.493833Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.498982Z","title":"A novel agent-based, evolutionary model for expressing the dynamics of creative open-problem solving in small groups","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.498982Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:fc6fdb624507f350527a4b2fce56a3c1c6f24ee85d09e623b7f0cc5afd533d92","observation_id":"f8b0632d-0d9b-4b0b-9a05-d8fb0bc702fd","resolution":{"observed_at":"2026-08-11T04:44:40.498982Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.503749Z","title":"Modeling Group Creativity as the Evolution of Community-level","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.503749Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:8c35abc56fc4a416e74277766ba791dcf5c571bec173b10131b627aae402b86b","observation_id":"3926122d-bd43-4791-b282-322c6495c1ff","resolution":{"observed_at":"2026-08-11T04:44:40.503749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.508690Z","title":"Understanding the Significance of Mid-Tier Research Teams in Idea Flow through a Community","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.508690Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:f808a7af2eb17420177acfa13644630870147928ddeaa257eec841d080ae9c2d","observation_id":"cd4e5d9b-73bb-4490-afe5-3c486c5263a5","resolution":{"observed_at":"2026-08-11T04:44:40.508690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.514241Z","title":"Combining Informetrics and Trend Analysis to Understand Past and Current Directions in Electronic Design Automa- tion","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.514241Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:db04a980a8a39a51361dc3f42ddf74d6fc6dfae0688aaff4259d6be0c4e465db","observation_id":"375b4f86-8abf-453b-bc58-084d5635734c","resolution":{"observed_at":"2026-08-11T04:44:40.514241Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.518860Z","title":"Towards Insightful Automated Dialog for Therapy through Top-down/Bottom-up Response Generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.518860Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:d77938b704763d320a47233027be6bed70a39c681ae8241e31020c4717c4bb74","observation_id":"2e2a12ca-5adb-4773-a2bf-4b9a3d9b9b14","resolution":{"observed_at":"2026-08-11T04:44:40.518860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.523507Z","title":"Toward an understanding of macrocognition in teams: Pre- dicting processes in complex collaborative contexts","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.523507Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:efdae8bd3729edc59f834cc867f0394f8c93a19e73df0e51b323e206a3d86813","observation_id":"2d6b15fb-9bab-4d49-9e66-921d629772aa","resolution":{"observed_at":"2026-08-11T04:44:40.523507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.528561Z","title":"Towards a generalized competency model of collaborative problem solving","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.528561Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:46c7764e7c655395b1c31cc326797a13215a94a79902b65ecb7a7022b89cec45","observation_id":"060029fe-02c7-4d4e-bdf8-2f8c5c0e1eee","resolution":{"observed_at":"2026-08-11T04:44:40.528561Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.533245Z","title":"How the group affects the mind: A cognitive model of idea generation in groups","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.533245Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:9b607aef4dd639b357411fcc865ef83c30d857e23990f447dfe5fb8e7d7a5123","observation_id":"9a5b5dc0-5fdf-43da-812f-e85ccb57acd4","resolution":{"observed_at":"2026-08-11T04:44:40.533245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.538492Z","title":"Understanding team learning dynamics over time","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.538492Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:3aad122bf07e86ef105adad58534d8a94523fdc3eecc9f3fe16196a78fa3c161","observation_id":"4b14adb9-9972-4851-8d10-44dbf075a27d","resolution":{"observed_at":"2026-08-11T04:44:40.538492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.543133Z","title":"Problem-solving phase transitions during team collaboration","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.543133Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:c9a9dbe6f1b150b631da03456065268c32f6ddb40e23163fd1a243d9d59c89c8","observation_id":"80180f3f-c055-4793-85c8-4c5cb3e22dea","resolution":{"observed_at":"2026-08-11T04:44:40.543133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.547945Z","title":"Team learning: Collectively connecting the dots","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.547945Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:8bda16e8862685c045b93cfc519b26981141d7db46cf3849462922f6cb38fbf3","observation_id":"01554114-bb32-4dda-99d8-bbb2a6212e8e","resolution":{"observed_at":"2026-08-11T04:44:40.547945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.552756Z","title":"Cognitive processes in well- defined and ill-defined problem solving","venue":null,"work_id":null,"year":1995},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.552756Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:f4c484a903c09dad3ce2e2b9af98e53118463b394813e1b38d595d162f763f48","observation_id":"a4de5a54-f9a8-41e2-8521-fa52f6165898","resolution":{"observed_at":"2026-08-11T04:44:40.552756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.557983Z","title":"Modeling semantic knowledge structures for creative problem solving: Studies on expressing concepts, categories, associations, goals and context","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.557983Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:5aff1e5a52231d4b6e8fbe34e13b0556efcd272cdb474373ef5db405db0294a2","observation_id":"75408f73-a294-4d47-9545-ced392c41f33","resolution":{"observed_at":"2026-08-11T04:44:40.557983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.562928Z","title":"The role of precedents in increasing creativity during iterative design of electronic embedded systems","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.562928Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:05b98e9edc8a02ea073f71fe1568da137c710d1668673a23050a622da2b6a36a","observation_id":"6cb7e9ce-5fb1-4b2d-9aa7-e7de3df671a6","resolution":{"observed_at":"2026-08-11T04:44:40.562928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.567526Z","title":"Not too much, not too little: The influence of constraints on creative problem solving","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.567526Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:027cee96268c746aea22789bcda9d7951282313f937a5d06a9f4a15a32945340","observation_id":"8ef5fbfa-8823-40b4-8402-b082bd51843d","resolution":{"observed_at":"2026-08-11T04:44:40.567526Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.572260Z","title":"Temporal construal effects on abstract and concrete thinking: Consequences for insight and creative cognition","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.572260Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:0e242accf831dc179638a2f186f6a1e0453c3e276a78552a03fc1466c936afb1","observation_id":"386d1d53-a198-40bb-94ed-8b2d508627f1","resolution":{"observed_at":"2026-08-11T04:44:40.572260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.577590Z","title":"Psychological safety and learning behavior in work teams","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.577590Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:44cd10b53bafea36c0d3bda39551bf6f03869fc4973fecec8f89a1728115c34b","observation_id":"8a259b8e-8053-4d50-84e5-a529d6aeefa8","resolution":{"observed_at":"2026-08-11T04:44:40.577590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.281848Z","title":"What do you mean by collaborative learning?","venue":null,"work_id":"77fc0c16-0f0f-4d40-8bee-4b7965adf419","year":1999},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.582063Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:0804ee722302d76e46f508eb13b3d2a89beee93ef6b0b23c7e65fe21c1d23d79","observation_id":"ba9d9c07-66e0-4b4c-a46f-bdd4194c34b6","resolution":{"observed_at":"2026-08-11T04:44:42.287216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.265141Z","title":"The use of environmental clues during incubation","venue":null,"work_id":"ffaa7168-1877-4394-aa62-af7271cfb164","year":2002},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.586172Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:564346762f2ad27b265a33f4bacd727fe6d240d114fc7060746ddd2c3d39a9a6","observation_id":"47282c87-c295-4fb3-b181-230d0d5bb3e1","resolution":{"observed_at":"2026-08-11T04:44:42.270325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.250348Z","title":"Climates and cultures for innovation and creativity at work","venue":null,"work_id":"dcd60edc-54bb-4b07-a815-e35fea44a2b6","year":2008},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.590492Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:05b8f0b1387b3efd6cf93e894bfb3f45bf4cdb1380c44a26aef73f4fe12e138f","observation_id":"978cc570-470a-47b0-8924-6d904faa4c9f","resolution":{"observed_at":"2026-08-11T04:44:42.255513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.234307Z","title":"Problem Framing Activities Carried Out by Student Design Teams to Enhance Creativity: Comparative Analysis of High and Low Creative Teams","venue":null,"work_id":"3eea81ab-2564-47ba-89e9-53a90514d7c7","year":2021},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.594763Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:e196e378d4346819f0306e925dc91dbec278d8a33d1a09e9e784e628ae3cd42e","observation_id":"eab1f725-ef5a-4cf8-a673-bc27a98e00db","resolution":{"observed_at":"2026-08-11T04:44:42.239864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.219013Z","title":"All Frames Are Not Created Equal: A Typology and Critical Analysis of Framing Effects","venue":null,"work_id":"1589f220-75e3-4ef6-b779-5058c815f175","year":1998},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.598738Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:27a9cd1a371d748d7188518cfcd2d31eaf5b27d35ed3c8e8a92a71fc633e67bd","observation_id":"5c5558bb-1a70-4a81-a32e-1e2a5faac798","resolution":{"observed_at":"2026-08-11T04:44:42.224423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.204361Z","title":"The framing effect and risky decisions: Examining cognitive functions with fMRI","venue":null,"work_id":"ff39fd89-3ccb-47f3-8fa0-696e8d6a3096","year":2005},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.602747Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:92df76e99ad4c431238a0a5391a9e65436a3b1926b1cc8aa2d3081e877f60c52","observation_id":"43953115-f26c-4627-bbae-370bdd1e7809","resolution":{"observed_at":"2026-08-11T04:44:42.209333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.188553Z","title":"Problem frame patterns: an exploration of patterns in the problem space","venue":null,"work_id":"7bd5e881-6c42-435f-aa0f-543d146eb484","year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.606706Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:ea38f2934c41e255e67c713805866f5936210e67c939759a7a2dee26459e7241","observation_id":"70a9ee0a-6db4-4e4f-981b-9aa5fc9c5787","resolution":{"observed_at":"2026-08-11T04:44:42.193930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.172455Z","title":"Two Minds, One Dialog: Coordinating Speaking and Understanding","venue":null,"work_id":"83f9a2d6-7b11-460f-9d8f-f0c853f5bf52","year":2010},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.611095Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:5e86b00972266d0ba3e29e889a053e43090afdfce0cb023bacb49c9bc64635c0","observation_id":"0e829ba8-b9cb-4e8a-a763-15fab8c05dd4","resolution":{"observed_at":"2026-08-11T04:44:42.178029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.149139Z","title":"Systematic Methodology for Design- ing Reconfigurable Delta Sigma Modulator Topologies for Multimode Communication Systems","venue":null,"work_id":"b74b2147-bfe3-4910-bbb6-0bd8badba121","year":2007},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.615264Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:f10ab19bf35a59050b5e4203d54caf9ecb114894f8de92dae5d075434b132193","observation_id":"42b7f0e8-7bff-4084-b23f-7889bebc3680","resolution":{"observed_at":"2026-08-11T04:44:42.162014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.122837Z","title":"High-Level Synthesis of Delta-Sigma Modu- lators Optimized for Complexity, Sensitivity and Power Consumption","venue":null,"work_id":"c9e1517f-af41-4ac8-ba1a-794f0b706ce2","year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.619647Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:2c42bae2b97f163ea958d1500a208a25db74d5bb850249136df8cd1f6ac6ba61","observation_id":"e82f8ac1-70ab-47f2-bd55-b3631791cee5","resolution":{"observed_at":"2026-08-11T04:44:42.133265Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.099664Z","title":"Learning and Memory. An Integrated Approach","venue":null,"work_id":"7b78cef3-2582-40cc-a0c8-b820449dec03","year":2000},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.624077Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:3b390d58917574cb4f8428583f5d23633b89c353ba4a605addb3d4d0568cc400","observation_id":"9ffb45c6-cb2b-42aa-923d-5eca50e93bf3","resolution":{"observed_at":"2026-08-11T04:44:42.108180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.080758Z","title":"Pragmatics in Analogical Mapping","venue":null,"work_id":"ffb83ca0-c1b6-40bb-8cea-268238e58ab4","year":1996},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.628722Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:934ec8da1581da4a65344563b48b6542eb9e9ba28636c5d17ba96c70fc56ae9c","observation_id":"f30b86e4-bc67-4a43-a8cb-d9d8e1203329","resolution":{"observed_at":"2026-08-11T04:44:42.087371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.064477Z","title":"Design, analogy, and creativity","venue":null,"work_id":"ffe48786-06bf-43c5-bedd-9fe80416575f","year":1997},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.633276Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:1ed917b9fc9f4d03b30097e6466a75632d6d9e9dc0d38be69208f4c532d43912","observation_id":"3589dce6-089d-4f1d-8a6d-877c54065924","resolution":{"observed_at":"2026-08-11T04:44:42.069816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.049885Z","title":"Cap- turing scientists’ insight from dddas","venue":null,"work_id":"ac9e622e-bd35-422a-abe6-d84bcba9d11a","year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.637791Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:168d2e6134fb82b0bae953e1bb3556f9e25e236935f3bbd4902af8f6148e9f64","observation_id":"7826dbf9-29be-416b-ae93-562f8e7a1469","resolution":{"observed_at":"2026-08-11T04:44:42.054917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.034942Z","title":"How scientists think: On-line creativity and conceptual change in science. Conceptual Structures and Processes: Emergence, discovery, and change","venue":null,"work_id":"c6667f1b-b264-49e1-9754-f2cdcd4fff99","year":1997},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.642526Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:c7414f159a9954783dfd0c887ef1432a552f73b7c783a91eb6af07dae6f586ca","observation_id":"89a5ae62-1ea1-4d1d-be16-97c82a4a43e9","resolution":{"observed_at":"2026-08-11T04:44:42.040183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1371/journal.pone.0182133","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:40.961011Z","title":"Creative foraging: An experimental paradigm for study- ing exploration and discovery","venue":null,"work_id":"95ecaab4-4321-4af8-beaa-c97848cfbad2","year":null},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.647280Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:d9f15f9f78bb0f65b58d150b21c336d2a0d64993a5fab78652c945dc60886b37","observation_id":"f9f5793f-1f43-457b-9cb8-59f416f69000","resolution":{"observed_at":"2026-08-11T04:44:40.968811Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.020865Z","title":"The design of divide and conquer algorithms","venue":null,"work_id":"d345c69d-0d98-4cc9-86e9-d6bc67aef27d","year":1985},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.652055Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:81a1ee231bccf8f7102b7de5f7aab2521bc5b9eec0bea4022600e6d7629334cc","observation_id":"e49de273-8ccc-4a4c-a08d-5f36ffbaa6ca","resolution":{"observed_at":"2026-08-11T04:44:42.025345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:42.006421Z","title":"Evocation and elaboration of solutions: Different types of problem-solving actions. An empirical study on the design of an aerospace artifact","venue":null,"work_id":"032dc26c-9775-4809-be73-196cf418646a","year":1991},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.656816Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:019de6f06207880450fe70c776bc9b35c27ab63da2d3a9600a8fceb41cfb6bca","observation_id":"41070aa1-6ae2-4b2f-a8bb-3d38196fd946","resolution":{"observed_at":"2026-08-11T04:44:42.011309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.991395Z","title":"Designing web sites: opportunistic actions and cognitive effort of lay-designers","venue":null,"work_id":"71ab4b87-18b3-456c-a166-5cf801520b0c","year":2003},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.661697Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:91bba8422542a2f908ebf611f3e66839fb6286d549feaa2f06ea024c6bcb4680","observation_id":"f779b46c-47a1-4409-bbc4-297890a1f7fe","resolution":{"observed_at":"2026-08-11T04:44:41.996427Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.976584Z","title":"Efficient creativity: Constraint-guided con- ceptual combination","venue":null,"work_id":"ed52e9aa-b959-4e4e-b3d7-f19411bc1469","year":2000},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.666309Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:2e7640c5f43f631d470e1d1ed625e653196e79567b9aa1bf2bebefd24ba570f9","observation_id":"7e7ab951-0e24-4871-bbb5-6fc5210f11e0","resolution":{"observed_at":"2026-08-11T04:44:41.981473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.962068Z","title":"Relations versus properties in concept combination. Journal of Memory and Language","venue":null,"work_id":"016f1b38-49d2-4fd7-ad56-b37e83417854","year":1998},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.670669Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:50e08c8cbf1dca9d5cb9f5a383f6a1a0fde972af190731d0abdeb7c7059e368a","observation_id":"f12ca863-d239-4568-a7cf-40b9bbb97940","resolution":{"observed_at":"2026-08-11T04:44:41.967456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.947246Z","title":"Effects of problem scope and creativity instructions on idea generation and selection","venue":null,"work_id":"ea3b327a-47d6-4307-bb3d-bc7ac26f852b","year":2014},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.675203Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:9a0d16f8a56178b433357aef1b9b33981ee44b662a8da85965e671cf5bfb1d16","observation_id":"4270fee9-6062-43f1-a5b8-1006f063ec1c","resolution":{"observed_at":"2026-08-11T04:44:41.952248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.932519Z","title":"Methodologies for examining problem solving success and failure","venue":null,"work_id":"4fad1d42-8b19-4930-a040-1cf25460b628","year":2007},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.679538Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:b4090b00158fe12011edf39cca99bed1ec20d0e80bf57af60457717976ce7be9","observation_id":"5e595907-c0b3-4585-83fd-0725447e01c3","resolution":{"observed_at":"2026-08-11T04:44:41.937322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.918566Z","title":"Critical Thinking Assessment in Engineer- ing Education: A Scopus-Based Literature Review","venue":null,"work_id":"9c4847e5-0322-4fd5-bc20-173461d9ec8f","year":2024},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.684220Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:ec745eb8a7185b7316d249cbe1ee56d83d078d7679d29b640b3c73124e2db3d6","observation_id":"9b4f35a9-31fb-4795-ba7b-cf09edec2a28","resolution":{"observed_at":"2026-08-11T04:44:41.923091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11308","last_updated":"2024-06-01T02:32:13Z","snapshot_observed_at":"2026-08-17T08:08:18.139352Z","submitted_at":"2023-05-18T21:10:58Z","title":"MCD: A Model-Agnostic Counterfactual Search Method For Multi-modal Design Modifications","version":2},"cited_work":{"arxiv_id":"2305.11308","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.11308","snapshot_observed_at":"2026-08-11T04:44:41.075804Z","title":"MCD: A Model-Agnostic Counterfactual Search Method For Multi-modal Design Modifications","venue":"cs.AI","work_id":"156d64c5-7d0b-47fd-b930-ba6ffb397dc5","year":2023},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.688576Z"},"links":{"cited_paper":"/paper/2305.11308","citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:a09e3b0c1236eb70a2d2855fce938eb972ecbfc636bc609d0c2129d777a1fe52","observation_id":"759b482c-6eca-4b14-9b89-f0ffef6ada9e","resolution":{"observed_at":"2026-08-11T04:44:41.081330Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.904770Z","title":"VisiFit: Structuring Iterative Improvement for Novice Designers","venue":null,"work_id":"94daf8d8-6d62-451c-88ad-0633e6b0e116","year":2021},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.693378Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:e657f738f91fb44c1df93ada433ad38778a8d3a3a722292ce61f01a7da26cebb","observation_id":"bc6cbdb5-a11a-4143-adac-b5acbe38cca1","resolution":{"observed_at":"2026-08-11T04:44:41.909096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.891046Z","title":"Mental fixation and metacognitive predic- tions of insight in creative problem solving","venue":null,"work_id":"8ddc49b5-864e-48a3-9a15-afe15ef6a80a","year":2015},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.697841Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:7debb4e79b6e119f2d416b386e593656777562bd9526b279e23f08e1becd778a","observation_id":"2707fb7e-7888-49c8-8530-26a7f0c01c1d","resolution":{"observed_at":"2026-08-11T04:44:41.895626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.876411Z","title":"Effects of task instructions and brief breaks on brainstorming","venue":null,"work_id":"29bf02d6-8147-4817-b513-01b9d205f536","year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.702300Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:10f6723774c659114324018187adbfac4bdbb196b1a9de2434faf623b9bb161d","observation_id":"94c98da4-a7e8-48b3-b227-90b9ec74220e","resolution":{"observed_at":"2026-08-11T04:44:41.881292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.861222Z","title":"Categorization and representation of physics problems by experts and novices","venue":null,"work_id":"25a561cd-1f12-4af2-8f64-1b025de1dc7d","year":1981},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.706583Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:64d2a7637058f308a2753aa74f4b1b08bd77316a9598923634d6339ea3f88e39","observation_id":"f67507c6-97a9-4026-bb0b-f0d213aa5536","resolution":{"observed_at":"2026-08-11T04:44:41.866110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.846574Z","title":"Social Neuroscience: People Thinking about Thinking People","venue":null,"work_id":"85cba52f-cde5-4243-97b9-4978ecad4426","year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.711038Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:8df1cdbe32f749638ec4fa151f9936ba80a6d6be9ef6bc200f2549bd36d04489","observation_id":"318dec8a-0f0d-45d1-90fe-67639df641c2","resolution":{"observed_at":"2026-08-11T04:44:41.851628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.830770Z","title":"Conflict across representational gaps: Threats to and opportunities for improved communication","venue":null,"work_id":"07100af8-0adf-48ca-ad78-1f81b7bce45c","year":2019},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.715295Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:e9abfd1d91a705e0fd3d3d67411cb6d2f91dfb78672928d87e1239555b8b1e11","observation_id":"6b2025f4-9e13-4438-a231-bc5172d9927d","resolution":{"observed_at":"2026-08-11T04:44:41.836362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.816174Z","title":"Joint Action: Mental Representations, Shared Information and General Mechanisms for Coordinating with Others","venue":null,"work_id":"87891751-783b-4324-8531-a2f0e490bfa2","year":2016},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.719917Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:a3bf4da1c4084660130afa3d622062576b01d62ffd77f1699d4716ed0c3a617c","observation_id":"ba37f0a8-a129-431c-bf96-8caf9bbb4a7d","resolution":{"observed_at":"2026-08-11T04:44:41.820746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.801300Z","title":"Social yet creative: The role of social relationships in facilitating individual creativity","venue":null,"work_id":"22416598-5e9e-40f9-ac1e-caeaa8de19ad","year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.724326Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:4353009e813c15f62f8be9f3147d86b28dfef8e128a98f37eb809aef2170c1b6","observation_id":"fad0abbf-860a-4bec-999d-6f3eeb2b97a2","resolution":{"observed_at":"2026-08-11T04:44:41.806054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.787291Z","title":"Making group brainstorming more effective: Recommendations from an associative memory perspective","venue":null,"work_id":"111f28d6-21d0-44ac-8a8a-d840f3d206f2","year":2002},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.728464Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:6f045fd7f0e199c2d8e574c0532f401cf2b7f74f714600fd723e08292e559afc","observation_id":"1bcfedb6-92af-4d35-bf6f-7a50e129a0ac","resolution":{"observed_at":"2026-08-11T04:44:41.792217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.772737Z","title":"Psychological safety, trust, and learning in organizations: A group-level lens. Trust and distrust in organizations: Dilemmas and approaches","venue":null,"work_id":"c184ecfe-c81a-4b48-b085-d5b98a520853","year":2004},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.732728Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:1ea7c980e92702afcf02de46ba26f2de95888c287a3dd288fcf4adc1522fbc28","observation_id":"b12c4eb5-3e46-4bdb-a39c-e1bd3f2dee48","resolution":{"observed_at":"2026-08-11T04:44:41.777627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.758429Z","title":"Recognizing devel- opers’ emotions while programming","venue":null,"work_id":"2f0f4998-4b6f-47f3-a6de-8a3ec53c23c8","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.736832Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:91455ac6667c3c333d81d6c61be722f494cbf66217b365783723a154f53cc632","observation_id":"5ba241d6-d64f-455e-91e3-9d75e148b4f3","resolution":{"observed_at":"2026-08-11T04:44:41.763067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.724909Z","title":"Negative affective environments improve com- plex solving performance","venue":null,"work_id":"557cebaf-4fed-4ae4-9dad-e7a65ea7d18f","year":2010},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.740704Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:2698abd6fe6ff9a2611ab9c32ed6b6969d0ebf324c26f2abfc88897a8cc39918","observation_id":"85ccd927-03f0-47bd-a2cc-da2dd27c8f06","resolution":{"observed_at":"2026-08-11T04:44:41.739654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.687798Z","title":"Exploring Causes of Frustration for Software Developers","venue":null,"work_id":"7c031f32-0846-4794-8c0d-53420ba6d970","year":2015},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.744610Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:02bd261ab601d4d363fccdd9dcead986e68dc65830c25c80f5703953f28f668b","observation_id":"10760aa5-b40d-4c24-8130-b4879ab0cc52","resolution":{"observed_at":"2026-08-11T04:44:41.704270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.661183Z","title":null,"venue":null,"work_id":"461581a2-1066-45a6-9eb2-e843ad896c49","year":2004},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.748628Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:f693b38db143a80495567637ef0839c403b9c376840508a255192ed30c17fc20","observation_id":"dd7a2b9c-067f-42fa-8c95-e930f7c7730b","resolution":{"observed_at":"2026-08-11T04:44:41.666135Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.644851Z","title":null,"venue":null,"work_id":"4c2bbc7c-cd46-42ac-b664-da1638d4be75","year":2021},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.752894Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:cbd4ccaea50f87d814b18415424bf084aa555c64e0c0d517e1c5b129644bcf7b","observation_id":"3ee7f64a-c451-4faa-9f7b-94a8a0a50d83","resolution":{"observed_at":"2026-08-11T04:44:41.649994Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.629315Z","title":null,"venue":null,"work_id":"07b5fdf0-e7eb-47a5-b478-ac4b38a92b8e","year":2024},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.756930Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:d2fe795b9ff2b7a84b68119ca9a9636bd70d5adb7c5c9ec033c80fc4505021e8","observation_id":"64c03ef0-9c88-4e63-972c-53b4ce86b1b9","resolution":{"observed_at":"2026-08-11T04:44:41.634281Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.597975Z","title":null,"venue":null,"work_id":"afa1a745-365a-4647-b7d1-bb344658e61f","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.764933Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:9bd146e0a542e73946fdb2fce9b051a4d5383032d29fbd95e180548821c93634","observation_id":"dca87000-a709-4a1d-b477-72c63ae75712","resolution":{"observed_at":"2026-08-11T04:44:41.602881Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.582239Z","title":null,"venue":null,"work_id":"42e1a513-14e4-491d-9cc0-5e2755ae41a1","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.768968Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:8080e0845e759e8fd50565dda564f00cfc6410efb29928d924ea613641999d41","observation_id":"3490fb26-05af-4eb4-985f-9304bde70f63","resolution":{"observed_at":"2026-08-11T04:44:41.587246Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.566960Z","title":null,"venue":null,"work_id":"61f7e702-c456-4325-b9b4-5074b133f7c3","year":2024},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.773360Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:36d40ece123751c62f17e156ba114802bd14967ac98aa7834567d8c9a54e4d1e","observation_id":"383a91a9-5206-498b-bf5e-e99bdeacff91","resolution":{"observed_at":"2026-08-11T04:44:41.571930Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.614582Z","title":null,"venue":null,"work_id":"c789ba91-bee9-467e-90b0-4159dd738614","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.777768Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:cd778ca799ad7ad72cdc489911973081c37c0ac33430110ba94d8b37a9869dac","observation_id":"e098edfd-bca1-460c-8f9c-29f17121942d","resolution":{"observed_at":"2026-08-11T04:44:41.619263Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.551586Z","title":null,"venue":null,"work_id":"5e4ca451-f5aa-442a-affd-89ede3c0914e","year":2014},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.781946Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:795789341194e7b649f146c55c1752f5520646a47d1afede5e198f13f53f778f","observation_id":"9e0ce951-0759-495c-9c26-ce887532bc4a","resolution":{"observed_at":"2026-08-11T04:44:41.556816Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.525755Z","title":"Multimodal expressive embodied conversa- tional agents","venue":null,"work_id":"87c8f9c8-31de-44fa-8140-cd348150056a","year":2005},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.786676Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:de04943b26b67aa6108e9bac162778814d34e8674109b59e5d45c793fe471d1b","observation_id":"a2e6bf0f-0e87-43fd-8e51-e6281df88146","resolution":{"observed_at":"2026-08-11T04:44:41.541219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.492229Z","title":"Zooming on Multimodality and Attuning. A Multilayer Model for the Analysis of the V ocal Act in Conversational In- teractions","venue":null,"work_id":"b9fa7301-e4cb-4337-a2ee-8787a13f5cf1","year":2006},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.790874Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:5e293a65583e35b12b22a8b70ddc7f6353cde0bff4743fb54c2e24ab4dac46be","observation_id":"7301c30e-c37a-4285-9259-dce0820db26c","resolution":{"observed_at":"2026-08-11T04:44:41.504650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.465957Z","title":"A Stacked Multi- Layered Perceptron - LLM Model for Extracting the Relations in Textual Descriptions","venue":null,"work_id":"086542b5-abf9-4d37-a7e8-5f41273f9179","year":2025},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.795185Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:a4df6be4dec6c027d4ae69999c2dc67745e04c2d296cff326d0f0da9391eccf2","observation_id":"0e81fd55-fe8f-4e23-833a-aaa325117076","resolution":{"observed_at":"2026-08-11T04:44:41.475152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.452044Z","title":"Towards Semantic Classification: An Experimental Study on Automated Understanding of the Meaning of Verbal Utterances","venue":null,"work_id":"30c99d4b-ce47-4c24-bf5a-b3bd2cd3c400","year":2025},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.799466Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:313df34d9023a595ef19a21bc155946e4057d5cd59ea34ee872c90991694f161","observation_id":"fbd18a57-c0fb-4b34-844e-dec65f220a5c","resolution":{"observed_at":"2026-08-11T04:44:41.456828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.437675Z","title":"T., Godfrey, J","venue":null,"work_id":"9bcb70ac-9b04-409b-8bb4-62687cba5541","year":1990},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.803612Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:2f80fe723dcb80fce068925928653bc40ae558bdac9e6296ce3e66680844d309","observation_id":"95b1f423-834f-4c8d-9eec-00701f55e070","resolution":{"observed_at":"2026-08-11T04:44:41.442461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.10190","last_updated":"2018-12-06T16:34:25Z","snapshot_observed_at":"2026-08-14T19:11:06.224746Z","submitted_at":"2018-05-25T15:04:17Z","title":"Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.10190","snapshot_observed_at":"2026-08-11T04:44:40.807994Z","title":"& Dureau, J","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.807994Z"},"links":{"cited_paper":"/paper/1805.10190","citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:42cd922a80944d73059e85a07b37bb72ca42a36ac81baaafa8d9568a4d899f38","observation_id":"a465aafb-4710-43e7-93d8-4de73f7ada0b","resolution":{"observed_at":"2026-08-11T04:44:40.807994Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.422778Z","title":"& Suleman, K","venue":null,"work_id":"e75f6784-63cb-44ae-9683-418d209d6fd0","year":2017},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.812693Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:0f02e853c03936bdb00e4f9d52be4b523b4129098b4e233af749b4e7545ab4c8","observation_id":"5a3ed98d-9352-4419-a412-216d992ef461","resolution":{"observed_at":"2026-08-11T04:44:41.427382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.407599Z","title":null,"venue":null,"work_id":"f1f4189c-7b1b-4cdd-a4b5-a43786f36c1d","year":2014},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.816991Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:79c4d0a2a979c03f13f5bab8a60a00dfd296a843ae5128f064bae03a766fedf2","observation_id":"373a0b20-3c28-4f58-a91e-212273028299","resolution":{"observed_at":"2026-08-11T04:44:41.412965Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.390821Z","title":"H., Tseng, B","venue":null,"work_id":"fe70fa4b-001a-4459-a30f-4890c1acd663","year":2018},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.821828Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:ffd021b4662e2f9e0d988edd5d3e99a69cf0e9f597d0b38dd6f6f7bed693b703","observation_id":"4438e7f1-8035-4265-984b-c0e52206217c","resolution":{"observed_at":"2026-08-11T04:44:41.396686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.374482Z","title":"S., Hoi, S","venue":null,"work_id":"cd3124a2-ef7a-40dc-a062-73a5abc111db","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.826261Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:94bf0d0cdac4e497752976e097428a42759d403432ad963de252738ac2a4f947","observation_id":"791665d0-5cdb-4dc8-bd36-b6ac350e41e8","resolution":{"observed_at":"2026-08-11T04:44:41.379245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.359526Z","title":"[Online]","venue":null,"work_id":"92882102-1bef-49ef-9feb-c0f0e06beecd","year":2024},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.830603Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:10e8ca6a7735fdabd82612914f06ce727175b6021bbdf17fdc4876a66694d899","observation_id":"676f94c2-4034-4707-93c0-3d6ac6a41e45","resolution":{"observed_at":"2026-08-11T04:44:41.364166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.343829Z","title":null,"venue":null,"work_id":"29e2d785-d5ac-4cde-8a1a-c39a50f33d19","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.834980Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:f4f94bd7eb4837d91bc8a80ea6678890fdb64c36fbfa604bbfc2bfcb118974df","observation_id":"756793be-6baa-41e8-a20d-2e1e48231136","resolution":{"observed_at":"2026-08-11T04:44:41.348468Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"cs/0306050","last_updated":"2003-06-12T12:35:00Z","snapshot_observed_at":"2026-08-14T13:00:08.537353Z","submitted_at":"2003-06-12T12:35:00Z","title":"Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"cs/0306050","snapshot_observed_at":"2026-08-11T04:44:40.839515Z","title":"F., & De Meulder, F","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.839515Z"},"links":{"cited_paper":"/paper/cs/0306050","citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:bec6797fdb12792521fd0cf97c838b1230b358607172bb25d3d78d31b437604b","observation_id":"df012027-dbf0-4c0f-ae7e-831cea1199e8","resolution":{"observed_at":"2026-08-11T04:44:40.839515Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.329667Z","title":"& Xue, N","venue":null,"work_id":"451cdc72-0b4d-48df-a271-d99dfed07838","year":2013},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.844527Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:d6124f892667200021ed33c3b0925651582303b9484014568d1bf62459ee52a1","observation_id":"2840e336-47c3-4921-9376-97208d615510","resolution":{"observed_at":"2026-08-11T04:44:41.334319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.316658Z","title":null,"venue":null,"work_id":"176f92b4-4309-4a64-aa13-7e4aa593ed13","year":2015},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.849274Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:5abf81414283b644986ebe1ee74fbeae7bfbc384deacb9d0bcbef5ed6c9c2a35","observation_id":"6891c6b8-2303-4f81-9387-255233b458c5","resolution":{"observed_at":"2026-08-11T04:44:41.320781Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.301823Z","title":"& Weber, F","venue":null,"work_id":"2fea86e9-eb37-4828-95aa-fcd382de3e48","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.853835Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:8fec1e5f551f4580b94b8c68391e9319ed6c1c3a96a884a3a9ca44e175549122","observation_id":"c7a7c285-b5de-4f4c-a9b8-9c0f662794c3","resolution":{"observed_at":"2026-08-11T04:44:41.306766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.287514Z","title":"H., Wu, S","venue":null,"work_id":"38c89439-1503-44be-a661-206350c16b01","year":2018},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.858690Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:0c612f77f6ca81631b6667301708527c9a000a9546aa25f64ff96ab9543dc370","observation_id":"a5d06a07-ae7e-4e36-be5c-b6ad14b92b8e","resolution":{"observed_at":"2026-08-11T04:44:41.292280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.273054Z","title":"& Toutanova, K","venue":null,"work_id":"73d45878-cd01-44d2-b3b7-bf86d08d0d1b","year":2019},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.863494Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:b3f309d45a2511b97b739edc4468ce1e8b5a54cab633b7b77f4c73c9ea61021b","observation_id":"abe0948a-3962-44ca-bab9-b163d309be39","resolution":{"observed_at":"2026-08-11T04:44:41.278076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.03670","last_updated":"2019-07-25T17:56:23Z","snapshot_observed_at":"2026-08-14T16:50:26.755237Z","submitted_at":"2019-04-07T15:24:32Z","title":"Speech Model Pre-training for End-to-End Spoken Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.03670","snapshot_observed_at":"2026-08-11T04:44:40.867977Z","title":"S., & Bengio, Y","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.867977Z"},"links":{"cited_paper":"/paper/1904.03670","citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:1564c039142cd249f90e17a103366d318a86671a58457746f35821069463bffe","observation_id":"4baa1ecd-4333-4fac-91df-0a4ca85a36e4","resolution":{"observed_at":"2026-08-11T04:44:40.867977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.08612","last_updated":"2018-05-30T06:52:06Z","snapshot_observed_at":"2026-08-16T22:21:12.958233Z","submitted_at":"2017-06-26T21:42:27Z","title":"VoxCeleb: a large-scale speaker identification dataset","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.08612","snapshot_observed_at":"2026-08-11T04:44:40.872981Z","title":"S., & Zisserman, A","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.872981Z"},"links":{"cited_paper":"/paper/1706.08612","citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:f650ed89fd452543e4cefa724fedd1f8f88be382497e93265bc0b0c1e9ff3cda","observation_id":"6dc11d81-3684-4b5f-97ef-8044020e0805","resolution":{"observed_at":"2026-08-11T04:44:40.872981Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.258584Z","title":null,"venue":null,"work_id":"84b5d9e1-aef0-4c9c-a785-b9143d685c37","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.877846Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:66220fc2e1ef69498dabdd5a395a336fa5cbc1df98c15ad39dbd8f3b2a2fb1a7","observation_id":"8a5ea5eb-3b76-44fe-b43c-dae8a3af0609","resolution":{"observed_at":"2026-08-11T04:44:41.263212Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.244189Z","title":null,"venue":null,"work_id":"1e8bc8a0-71ed-4186-9d94-b11f9608f2c9","year":2020},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.882165Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:72016164e6066c508ca5c7e5e672ca981c83d2804d8845b994bcacdf3e972103","observation_id":"88714745-1d91-4fcf-b684-0f63f69a7d2f","resolution":{"observed_at":"2026-08-11T04:44:41.248884Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.03209","last_updated":"2018-04-09T19:58:17Z","snapshot_observed_at":"2026-08-15T16:28:51.252929Z","submitted_at":"2018-04-09T19:58:17Z","title":"Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.03209","snapshot_observed_at":"2026-08-11T04:44:40.886567Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.886567Z"},"links":{"cited_paper":"/paper/1804.03209","citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:0456fdc05d83fb9e0c7217c0f9504b51f207cab5d86c7ff4416529007ec9e4d7","observation_id":"111f9f7d-3fdd-401f-a9f1-3f33a447ade3","resolution":{"observed_at":"2026-08-11T04:44:40.886567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.229130Z","title":"& Dupoux, E","venue":null,"work_id":"00bfe703-36b9-436c-bb27-829076f25b33","year":2021},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.891101Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:7da9db7bf8acc3c651d0eea90817e9fbb54cf22049c7c578e64a5e77d4c484fc","observation_id":"db47aeab-f279-4b88-90c3-920104961963","resolution":{"observed_at":"2026-08-11T04:44:41.234021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.214726Z","title":null,"venue":null,"work_id":"b08e5897-c776-4b3d-8c83-a250753c5aed","year":2014},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.895360Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:1e1c9cd0dfab3dd07bf93592ce7f033ffafa1b8d4bef8be4fd1d009f66789eae","observation_id":"3f05929f-b2ec-4393-a509-402b6a8aa444","resolution":{"observed_at":"2026-08-11T04:44:41.219449Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.201138Z","title":"& Wellner, P","venue":null,"work_id":"592b22f4-d57c-4136-a292-9c9c7be1e75d","year":2005},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.899119Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:2ebc28b6f5fd0d5af6c3765c3c39691c7eed94ac76a4c8be2727acc7df1823b9","observation_id":"18930852-22dc-416d-94ff-c5373a4476d8","resolution":{"observed_at":"2026-08-11T04:44:41.205467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.187442Z","title":null,"venue":null,"work_id":"abfc3f66-d8e7-4581-9adf-3cf8837148e1","year":2011},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.903129Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:33037d684eb4da41683c665e59a7db0b7877df3a44fdca1e40045d0b508b7094","observation_id":"3579b17e-dbe5-4810-9c97-eab5f7db3b7c","resolution":{"observed_at":"2026-08-11T04:44:41.191628Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.173044Z","title":null,"venue":null,"work_id":"3439d001-a3b1-41cf-bb5e-85e942a63d81","year":2016},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.907289Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:7edd1f4f385d5ce20cb428310c8e0bbc88d237c62e18b13f2eb8ce4b56a1c7c5","observation_id":"076edf09-5e37-4e98-8ac6-0280fa263782","resolution":{"observed_at":"2026-08-11T04:44:41.177662Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.155332Z","title":null,"venue":null,"work_id":"71947c5c-4594-42ac-abe7-78cf2ec2f80a","year":2024},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.911326Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:bce43e0299d9033d70372b82fb1525e8e4e545e381a3c2f1c00f47d613c6c52a","observation_id":"d8f04de4-7ffd-4c92-94ff-53048e8cdb22","resolution":{"observed_at":"2026-08-11T04:44:41.161615Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.139635Z","title":null,"venue":null,"work_id":"9ccb6d5b-d59f-4961-abe8-a654ac3e3b7a","year":2023},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.915171Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:ec84522aecc44354cb17137940adc41aa7327e8fadbc5c4d78df6d776349c128","observation_id":"4c21b8af-2638-44c5-be97-0311a06a17d6","resolution":{"observed_at":"2026-08-11T04:44:41.144697Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.124102Z","title":null,"venue":null,"work_id":"ce91a7eb-a581-48f7-8a22-4f69d18aa51c","year":2023},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.919110Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:5e3d3c7c1998e745672b14540e62d8deb6dc58dc39dbe7ff4350ec458d0bde67","observation_id":"3ecf52ad-1235-4b90-bc08-775733c2c9e3","resolution":{"observed_at":"2026-08-11T04:44:41.128861Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.108140Z","title":null,"venue":null,"work_id":"7048b598-9df0-45c2-9ee7-1ca9e8c76ea2","year":2023},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.923031Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:44d00552372965dc16426a227180a2e276cf6300c7517fcdfab4fb32c0c951eb","observation_id":"8cdbf409-5295-4a87-8722-45c43463a577","resolution":{"observed_at":"2026-08-11T04:44:41.112903Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:44:41.092151Z","title":null,"venue":null,"work_id":"63f1b0dc-7b8b-47bb-9aba-835dd2be03f2","year":2019},"citing_paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-11T04:44:40.927495Z"},"links":{"citing_paper":"/paper/2412.18489"},"observation_digest":"sha256:22564f7a8ec1bad9955f8a46dbe480c71feee64579826c9d786a2ef58f7a15fa","observation_id":"74a747b4-48e2-42f6-83d7-6aa1dbbbd9e7","resolution":{"observed_at":"2026-08-11T04:44:41.097256Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.18489","last_updated":"2024-12-24T15:22:10Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-17T03:22:12.379865Z","submitted_at":"2024-12-24T15:22:10Z","title":"An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving"},"reference_resolution":{"displayed":99,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":45,"verified_exact":2,"verified_fuzzy":51},"total_outbound_references":99},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 99 of 99 outbound references and 0 inbound Pith citation observations for arXiv:2412.18489."}