{"as_of":"2026-08-10T08:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1d0849e9b13d5e3a885056e78d118421f61338e62122900dea9fd9c2a24a045b","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:55:17.713778Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-23T22:05:50.420898Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":"2108.00316","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T.; Agu, N","venue":null,"work_id":"ae48dfd2-2191-44f7-b8be-cca5295bcf13","year":2021},"citing_paper":{"arxiv_id":"2408.16213","last_updated":"2024-08-29T02:12:58Z","snapshot_observed_at":"2026-08-02T05:05:13.711617Z","submitted_at":"2024-08-29T02:12:58Z","title":"M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-05-23T22:03:33.418989Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2408.16213"},"observation_digest":"sha256:b0754ccb2d4129f96b19783dfae81727ab67e974b4fc48e4f7a4477d2cf8cbdd","observation_id":"b8ec269e-3e04-4a60-9114-c69e6cbbb03b","resolution":{"observed_at":"2026-05-23T22:05:50.423591Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-08-06T18:55:17.713778Z","title":"https://api.semanticscholar.org/CorpusID:235420881","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.06959","last_updated":"2025-07-09T15:40:18Z","snapshot_observed_at":"2026-08-07T10:43:27.957447Z","submitted_at":"2025-07-09T15:40:18Z","title":"CheXPO: Preference Optimization for Chest X-ray VLMs with Counterfactual Rationale","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T18:55:17.713778Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2507.06959"},"observation_digest":"sha256:d867c6026ef6e39b39b24ff6d4dafe88b12c9a92458e7351d85b091ca1e355c2","observation_id":"bfedf9de-f54e-4df7-9d27-67d784c0c22e","resolution":{"observed_at":"2026-08-06T18:55:17.713778Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-08-06T18:54:39.844159Z","title":"arXiv preprint arXiv:2108.00316 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.06992","last_updated":"2025-08-21T02:47:04Z","snapshot_observed_at":"2026-08-07T11:49:46.000419Z","submitted_at":"2025-07-09T16:15:38Z","title":"MCA-RG: Enhancing LLMs with Medical Concept Alignment for Radiology Report Generation","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T18:54:39.844159Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2507.06992"},"observation_digest":"sha256:84158d7eeef2a6c7fb984d71a45df2bf65a792008672ddb736e846b8d7977e05","observation_id":"d9915f99-2f8e-4421-86f2-df2f6b1a885e","resolution":{"observed_at":"2026-08-06T18:54:39.844159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-08-06T16:51:17.983824Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.12461","last_updated":"2025-07-16T17:58:35Z","snapshot_observed_at":"2026-08-09T14:12:21.532602Z","submitted_at":"2025-07-16T17:58:35Z","title":"Interpreting Radiologist's Intention from Eye Movements in Chest X-ray Diagnosis","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:17.983824Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2507.12461"},"observation_digest":"sha256:818172c4a241b3fff4338cf46e481224ec6b3bd31a1509f93add667aa104b2a4","observation_id":"077a41d2-6040-4dbd-b24e-d071920c2f20","resolution":{"observed_at":"2026-08-06T16:51:17.983824Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-08-05T23:56:50.057351Z","title":"Chest imagenome dataset for clinical reasoning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.04572","last_updated":"2025-08-06T15:54:44Z","snapshot_observed_at":"2026-08-09T16:58:26.710423Z","submitted_at":"2025-08-06T15:54:44Z","title":"Knowledge to Sight: Reasoning over Visual Attributes via Knowledge Decomposition for Abnormality Grounding","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T23:56:50.057351Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2508.04572"},"observation_digest":"sha256:925fa3929829c347c987c42ac316044e39ddc5f4e405599f6257cfe50fdda023","observation_id":"3b8b3740-96ed-4432-82a3-c7f284912c34","resolution":{"observed_at":"2026-08-05T23:56:50.057351Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":"2108.00316","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T.; Agu, N","venue":null,"work_id":"ae48dfd2-2191-44f7-b8be-cca5295bcf13","year":2021},"citing_paper":{"arxiv_id":"2510.04142","last_updated":"2026-05-11T11:36:03Z","snapshot_observed_at":"2026-08-05T21:53:11.988931Z","submitted_at":"2025-10-05T10:42:21Z","title":"Turning Drift into Constraint: Robust Reasoning Alignment in Non-Stationary Multi-Stream Environments","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-18T10:44:31.842696Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2510.04142"},"observation_digest":"sha256:e88f1a1fd6b846120d9e4cb7769b12fd47cabd7ebc53ce51c9f07cafc84ebac7","observation_id":"952bd33d-aadc-4682-95a2-95b3a8a5d3e2","resolution":{"observed_at":"2026-05-18T10:46:17.207908Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-08-03T12:25:51.568337Z","title":"arXiv preprint arXiv:2108.00316 (2021) 8, 9","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.03191","last_updated":"2026-05-23T10:05:21Z","snapshot_observed_at":"2026-08-09T16:56:17.744290Z","submitted_at":"2026-01-06T17:13:23Z","title":"AnatomiX, an Anatomy-Aware Grounded Multimodal Large Language Model for Chest X-Ray Interpretation","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T12:25:51.568337Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2601.03191"},"observation_digest":"sha256:e86bf3c1f3a052018dc56cfd8b0fe8b3095bcc1c0108071790d40b40939e9e84","observation_id":"fd4e0bc4-2503-406c-bffb-5d4b1308490c","resolution":{"observed_at":"2026-08-03T12:25:51.568337Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-08-03T08:48:02.748524Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.15891","last_updated":"2026-05-26T06:03:02Z","snapshot_observed_at":"2026-08-09T03:36:35.642368Z","submitted_at":"2026-01-22T12:11:53Z","title":"RadJEPA: Radiology Encoder for Chest X-Rays via Joint Embedding Predictive Architecture","version":3},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-03T08:48:02.748524Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2601.15891"},"observation_digest":"sha256:54733a15573c48921cfdb7835ef88207fffb316fb3895e478e4eae0c0e8a08d5","observation_id":"1dbc742a-81a4-4ef2-82a0-e3b632655910","resolution":{"observed_at":"2026-08-03T08:48:02.748524Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":"2108.00316","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T.; Agu, N","venue":null,"work_id":"ae48dfd2-2191-44f7-b8be-cca5295bcf13","year":2021},"citing_paper":{"arxiv_id":"2604.04563","last_updated":"2026-04-07T22:05:38Z","snapshot_observed_at":"2026-08-03T23:40:45.588378Z","submitted_at":"2026-04-06T09:52:26Z","title":"Temporal Inversion for Learning Interval Change in Chest X-Rays","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T19:23:46.184189Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2604.04563"},"observation_digest":"sha256:263797b61605375f05c5a892525285b5c06fd5c1d6b2092850914370d9dde107","observation_id":"3f4031a9-7734-4e60-8a58-02f484176d03","resolution":{"observed_at":"2026-05-10T23:00:50.508194Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":"2108.00316","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T.; Agu, N","venue":null,"work_id":"ae48dfd2-2191-44f7-b8be-cca5295bcf13","year":2021},"citing_paper":{"arxiv_id":"2605.11304","last_updated":"2026-05-11T22:47:24Z","snapshot_observed_at":"2026-07-06T23:23:11.928199Z","submitted_at":"2026-05-11T22:47:24Z","title":"CheXTemporal: A Dataset for Temporally-Grounded Reasoning in Chest Radiography","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-13T06:06:44.019029Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2605.11304"},"observation_digest":"sha256:52d36fce1e411d16850fe24e83de7ac15763ad96f041c61f636f9211c6569166","observation_id":"cb4a9157-cf84-45d7-8500-fd91dac5280e","resolution":{"observed_at":"2026-05-13T06:07:22.217981Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00316","snapshot_observed_at":"2026-08-04T00:54:37.167649Z","title":"Chest imagenome dataset for clinical reasoning.arXiv preprint arXiv:2108.00316, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.00279","last_updated":"2026-07-31T20:31:19Z","snapshot_observed_at":"2026-08-09T03:34:11.867994Z","submitted_at":"2026-07-31T20:31:19Z","title":"Learning to See Locally and Align Clinically with Pathology Semantics for Radiology Report Generation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-04T00:54:37.167649Z"},"links":{"cited_paper":"/paper/2108.00316","citing_paper":"/paper/2608.00279"},"observation_digest":"sha256:ad45bd6a8e0eda5e68552047691d183221c2c6cf1431b36c0633caf00784b8ae","observation_id":"65bd577b-b453-4438-90ef-72adbf5ba585","resolution":{"observed_at":"2026-08-04T00:54:37.167649Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2108.00316/citation-record","integrity":"/paper/2108.00316/integrity","json":"/paper/2108.00316/citation-record.json","paper":"/paper/2108.00316"},"outbound":[],"paper":{"arxiv_id":"2108.00316","last_updated":"2021-07-31T20:10:30Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T16:57:52.926996Z","submitted_at":"2021-07-31T20:10:30Z","title":"Chest ImaGenome Dataset for Clinical Reasoning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2108.00316."}