{"as_of":"2026-08-21T10:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7b0e903ef4c63905d9791158dea2ada4dafbddbd2ea1ae7e5706b2de355e2ab9","coverage":[{"denominator":10,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:00:00.565731Z","state":"measured"},{"denominator":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2506.11082/citation-record","integrity":"/paper/2506.11082/integrity","json":"/paper/2506.11082/citation-record.json","paper":"/paper/2506.11082"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:00:00.783904Z","title":"Transforming Disease Prediction with LotusAI-Predict: A Fine-Tuned LLaMA Model","venue":null,"work_id":"6fdc44db-614c-43ad-9fdf-223d02d4baeb","year":2025},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.520400Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:d893c32af572858e1cbdcbdc231960036a8fd7b84ae8e34e2c3158cd602c637f","observation_id":"7322cab6-f82d-4d01-8c04-24d51afccae7","resolution":{"observed_at":"2026-08-07T11:00:00.788843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T11:00:00.769722Z","title":"A Transformer-Based Model for Zero- Shot Health Trajectory Prediction","venue":null,"work_id":"d2d17bf5-8416-4dcd-ae24-9f3b3c83e0b6","year":2024},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.525786Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:430309e099d8cabe5b6405010eece459b43f79257d333f947667a66f3b79543a","observation_id":"0f10dda1-f3f1-4578-a5b6-c70b722b0904","resolution":{"observed_at":"2026-08-07T11:00:00.774249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.15827","last_updated":"2024-08-28T14:40:15Z","snapshot_observed_at":"2026-08-16T13:23:11.281145Z","submitted_at":"2024-08-28T14:40:15Z","title":"Automatic Differential Diagnosis using Transformer-Based Multi-Label Sequence Classification","version":1},"cited_work":{"arxiv_id":"2408.15827","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.15827","snapshot_observed_at":"2026-08-07T11:00:00.672880Z","title":"Automatic Differential Diagnosis using Transformer-Based Multi-Label Sequence Classification","venue":"cs.LG","work_id":"ef5c82c1-de75-41ab-b0e4-a3b00a6f06bf","year":2024},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.530524Z"},"links":{"cited_paper":"/paper/2408.15827","citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:a5a2f1356fb1b7a30013aced8bf606fcf56c9548f804852321ce385a46e9c07d","observation_id":"b98e198f-db1e-46ba-af7c-7ba731dc3bf3","resolution":{"observed_at":"2026-08-07T11:00:00.682244Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T11:00:00.753252Z","title":"Sequential Diagnosis Prediction with Transformer and Ontological Representation","venue":null,"work_id":"384d47f6-99d0-4fbc-ba8e-fc73087e7ddc","year":2023},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.535647Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:421a18f99c60c99cbd7d24972e0bbf45af5a9e922c6abb9e63c2b1eb53482079","observation_id":"346bb7a0-be1d-4aef-9d83-cbc48ef14a9f","resolution":{"observed_at":"2026-08-07T11:00:00.758157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T11:00:00.738439Z","title":"Transformer-Based Deep Learning Model for the Diagnosis of Lung Cancer in Primary Care","venue":null,"work_id":"8a8b76b1-715d-4163-b96f-5948764e9cfb","year":2024},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.541245Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:9c6df627edfa4d7e789cae358bda00d1d3071cace58a85f50a234e0df6954fc5","observation_id":"7abc5681-ad84-4305-b547-207d7d1e7553","resolution":{"observed_at":"2026-08-07T11:00:00.743127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T11:00:00.723221Z","title":"Variational probabilistic inference and the QMR-DT network","venue":null,"work_id":"322ae7d4-1a8c-452a-955f-f3eca70d0380","year":1999},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.546609Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:cf4013c9e6ef1abaaca5702b50123ea367f6a114cb6dee2337ce4691e0969e02","observation_id":"eb66c491-3d0d-4155-9b3c-bba882877b5b","resolution":{"observed_at":"2026-08-07T11:00:00.727954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:00:00.551684Z","title":"MIMIC-IV, a freely ac- cessible electronic health record dataset","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.551684Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:a0fefcdd06f1a039779f67454305ad1bd479e5299825271a8ef7fca23351e050","observation_id":"a85db647-330a-40fd-aea2-4a6b9df7dae9","resolution":{"observed_at":"2026-08-07T11:00:00.551684Z","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":"2026-08-07T11:00:00.556590Z","title":"Artificial Intelligence and Internet of Things Enabled Disease Diagnosis Model for Smart Healthcare Systems","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.556590Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:4f24e920b090515fa2469dca13e06e7681741ccb8819f440e49ed3a432b18d4d","observation_id":"dee0cbe5-2c0a-448b-8875-92a0696cf0c1","resolution":{"observed_at":"2026-08-07T11:00:00.556590Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:00:00.707818Z","title":"Empirical evalua- tion of performance degradation of machine learning- based predictive models–A case study in healthcare information systems","venue":null,"work_id":"5519f333-081b-4859-ac35-1a99c2c2b81b","year":2022},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.561092Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:706982c3742b8c250ab4c0b3444afdf8625bb1cb7117a061c008b1d0c1a7c539","observation_id":"b7544a62-71eb-4bc3-80ce-da932a2c782d","resolution":{"observed_at":"2026-08-07T11:00:00.712757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T11:00:00.692565Z","title":"Diag- nostic Prediction with Sequence-of-Sets Representation Learning for Clinical Events","venue":null,"work_id":"adeb03b9-9ce6-436f-a953-965e5855b2f8","year":2020},"citing_paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:00.565731Z"},"links":{"citing_paper":"/paper/2506.11082"},"observation_digest":"sha256:b6f738e9ca8530331cd9f0dc6aa95379ccd1775bb7fd5d431e411e00a259a846","observation_id":"5de7a605-2e73-4763-9775-2937ad51f678","resolution":{"observed_at":"2026-08-07T11:00:00.697143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.11082","last_updated":"2025-06-04T08:48:32Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-15T17:57:38.518432Z","submitted_at":"2025-06-04T08:48:32Z","title":"PRISM: A Transformer-based Language Model of Structured Clinical Event Data"},"reference_resolution":{"displayed":10,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":1,"verified_fuzzy":7},"total_outbound_references":10},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2506.11082."}