{"as_of":"2026-08-14T09:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6d6c5487294834364fcf5b7ccd568a33bfaebaec31bd74c146ed0bdd5d4798c9","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:46:20.163265Z","state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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/2505.17661/citation-record","integrity":"/paper/2505.17661/integrity","json":"/paper/2505.17661/citation-record.json","paper":"/paper/2505.17661"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.20268","last_updated":"2025-04-28T11:50:42Z","snapshot_observed_at":"2026-08-12T22:14:34.277092Z","submitted_at":"2024-10-26T20:39:41Z","title":"Centaur: a foundation model of human cognition","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.20268","snapshot_observed_at":"2026-08-07T14:46:18.377131Z","title":"Centaur: a foundation model of human cognition","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:18.377131Z"},"links":{"cited_paper":"/paper/2410.20268","citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:0c7eaf83198803f2d5ef755490ca753dff67e95a36c17efd47928ed90e311dc4","observation_id":"72b14718-9478-48f1-ae15-efab42444728","resolution":{"observed_at":"2026-08-07T14:46:18.377131Z","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":"2026-08-07T14:46:22.397383Z","title":"Using large-scale experiments and machine learning to discover theories of human decision-making","venue":null,"work_id":"c03f9146-ca41-420a-b428-3c257ba6b171","year":2021},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:18.508748Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:e21a516a25f3510136728f918f465fb782d52b3f9d8bc5e9fb44750c46f20bfb","observation_id":"c0c2d12c-8762-43d1-9024-40e48367e994","resolution":{"observed_at":"2026-08-07T14:46:22.449702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:22.257453Z","title":"Hybrid neural-cognitive models reveal how memory shapes human reward learning, 2024","venue":null,"work_id":"843f4a6b-1660-4a44-9ab8-c65322f607b1","year":2024},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:18.620334Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:df4c69d3120be95efd2007135cbcda103c4060b0b10183bf7bfe7ff5c1f4d28b","observation_id":"da9ee55d-8e44-498a-9b04-809d1d3b8546","resolution":{"observed_at":"2026-08-07T14:46:22.334951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:22.096196Z","title":"Scaling up psychology via scientific regret minimization","venue":null,"work_id":"dafd94dc-7eee-4fad-b9d8-d072c6f36925","year":2020},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:18.828065Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:5bc8939dbd0d6bd1dcd21ed0919e49d161794cca5c16b57b50ba8fc5c52f1b36","observation_id":"76954d95-8488-4782-9678-0c7d3f6c8c0c","resolution":{"observed_at":"2026-08-07T14:46:22.173225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-13T15:58:13.809876Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-07T14:46:18.960936Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:18.960936Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:b164b9de5accf20314c9681880b371c504cf601ff7b6e1b943c6cbd29c0edf5d","observation_id":"fe16738a-9303-46e4-8264-da0c3276c81d","resolution":{"observed_at":"2026-08-07T14:46:18.960936Z","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":"2026-08-07T14:46:21.950002Z","title":"Qwen3 technical report","venue":null,"work_id":"2ca9cf3a-1464-4730-99f9-0a9485c45662","year":2025},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.197251Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:2b1a55d3320cd5e597cf41797e0aac6ed5ec7a143b5773a113964a7ae9e60278","observation_id":"4f50b87b-6c8f-4965-b9f1-c87dbe0359b3","resolution":{"observed_at":"2026-08-07T14:46:22.029537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:21.792678Z","title":"Closed-loop scientific discovery in the behavioral sciences","venue":null,"work_id":"27a2fc3c-7dfd-480f-9465-ce5d87d69330","year":2024},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.317154Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:5fe37947a4a5a2cd342cecba10b64ff845efe961a0d6b1fd69c5a69942dc7402","observation_id":"6f6a1b29-7c58-457a-a3fa-6f5e810fc591","resolution":{"observed_at":"2026-08-07T14:46:21.852826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:21.621729Z","title":"How should the advancement of large language models affect the practice of science? Proceedings of the National Academy of Sciences, 122 0 (5): 0 e2401227121, 2025","venue":null,"work_id":"4d541daf-f606-4e95-b4a2-e4b415be4113","year":2025},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.500433Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:3ed49d34603814fb354646bb40634604b90bf00bc10b32486a516e898505e78b","observation_id":"ea6efe0d-2dc0-41b3-b057-7bad14d05f7b","resolution":{"observed_at":"2026-08-07T14:46:21.711365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:21.414580Z","title":"Automating the practice of science: Opportunities, challenges, and implications","venue":null,"work_id":"5756edd3-0bcc-4c8e-8088-0c769b523cd3","year":2025},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.616915Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:85b2f66dc17555766c2896895fc9654e6f60604168e2af215ffa7c327d990208","observation_id":"f15ba319-60e4-4807-a5d3-4428423293fd","resolution":{"observed_at":"2026-08-07T14:46:21.518861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:21.264139Z","title":"Discovering symbolic cognitive models from human and animal behavior","venue":null,"work_id":"4f9154c2-d4cc-48fe-ae62-2c1053f91b9f","year":2025},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.693437Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:193d7af50559deb68e003ae900d7fbb1250502194ca393f21b5d8e7630588e42","observation_id":"44757967-9be0-4871-bc55-4e33ed840e76","resolution":{"observed_at":"2026-08-07T14:46:21.336206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:19.782950Z","title":"Towards automation of cognitive modeling using large language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.782950Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:b8e6f99699d6da54f98994e07ce3c1da058a969b3087706e577cf392e4c23c5e","observation_id":"68c05dcb-b909-45c1-ae71-9623034242db","resolution":{"observed_at":"2026-08-07T14:46:19.782950Z","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":"2026-08-07T14:46:21.103192Z","title":"Generalized outcome-based strategy classification: Comparing deterministic and probabilistic choice models","venue":null,"work_id":"f2311726-848c-460b-b82d-918397acb484","year":2014},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.904599Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:09773e218641f0e25e044280a88e257d5d60ba8d4d14d14d741b90ce6c809aed","observation_id":"d108c10f-2c9e-488e-98d0-e9087dbf5dc3","resolution":{"observed_at":"2026-08-07T14:46:21.171749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:20.933949Z","title":"Simple heuristics that make us smart","venue":null,"work_id":"27e604af-b5b5-4fcc-8962-1cf9681a3e4e","year":2000},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:19.996221Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:8152638546a2a2578101605f7bb10b96c4e78209863709f3626802a44013c3ae","observation_id":"643795a9-e77d-466a-9f52-3b7e560c5e17","resolution":{"observed_at":"2026-08-07T14:46:21.029001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:20.691036Z","title":"Heuristics from bounded meta-learned inference","venue":null,"work_id":"c67acd59-bb3b-4d89-a2b8-f79ee02f18bf","year":2022},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:20.076972Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:a41e06a1084b750ed38d1dfce7609aa8647b73f80db31f66b672946b89d388e2","observation_id":"e631c507-f039-494a-a8bc-e2116033cb21","resolution":{"observed_at":"2026-08-07T14:46:20.836308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T14:46:20.456945Z","title":"Heuristics as bayesian inference under extreme priors","venue":null,"work_id":"6e2d0e8e-e0e1-411a-b279-1e24db3b6654","year":2018},"citing_paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:20.163265Z"},"links":{"citing_paper":"/paper/2505.17661"},"observation_digest":"sha256:c8d7f8290f520a9caccbea59dadc5ec568e27a0b85c6547da0180dfddc1dfe31","observation_id":"dd78af60-2b42-4b84-9d17-83ed71c9dbda","resolution":{"observed_at":"2026-08-07T14:46:20.528981Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.17661","last_updated":"2025-05-23T09:26:43Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T14:40:39.691674Z","submitted_at":"2025-05-23T09:26:43Z","title":"Automated scientific minimization of regret"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":12},"total_outbound_references":15},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2505.17661."}