{"as_of":"2026-08-12T20:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6c10a78b6a28cf54f90ba5b3974513b0d709e165fd114a513a05be68ac6b3f1b","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":"2026-08-07T00:24:25.735607Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T06:30:16.612345Z","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":"2026-05-18T13:42:38.510283Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"cited_work":{"arxiv_id":"2506.14142","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14142","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mllm-as-a-judge: Assessing multimodal llm-as-a-judge with vision- language benchmark","venue":null,"work_id":"ebcfc1db-1baa-4c66-b424-458bd1210741","year":2025},"citing_paper":{"arxiv_id":"2509.20490","last_updated":"2026-04-15T03:26:59Z","snapshot_observed_at":"2026-08-02T13:44:47.619708Z","submitted_at":"2025-09-24T19:08:01Z","title":"RadAgents: Multimodal Agentic Reasoning for Chest X-ray Interpretation with Radiologist-like Workflows","version":4},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-18T13:42:27.605436Z"},"links":{"cited_paper":"/paper/2506.14142","citing_paper":"/paper/2509.20490"},"observation_digest":"sha256:fbab65b429ed640e80e23fedd161ea9c6b40bc906f2366b2c5597ca674170c49","observation_id":"8af27dcf-5f1d-4ea8-a042-14c445a3b086","resolution":{"observed_at":"2026-05-18T13:42:38.514773Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"cited_work":{"arxiv_id":"2506.14142","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14142","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mllm-as-a-judge: Assessing multimodal llm-as-a-judge with vision- language benchmark","venue":null,"work_id":"ebcfc1db-1baa-4c66-b424-458bd1210741","year":2025},"citing_paper":{"arxiv_id":"2604.02695","last_updated":"2026-04-03T03:39:30Z","snapshot_observed_at":"2026-08-11T03:25:02.285839Z","submitted_at":"2026-04-03T03:39:30Z","title":"XrayClaw: Cooperative-Competitive Multi-Agent Alignment for Trustworthy Chest X-ray Diagnosis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-13T21:00:18.392949Z"},"links":{"cited_paper":"/paper/2506.14142","citing_paper":"/paper/2604.02695"},"observation_digest":"sha256:0259bfe3324ddcda460567c0525eb61e75e53d23a0390e4e761564d8d3930ffc","observation_id":"5cb49239-2d61-4830-a797-0755da13780a","resolution":{"observed_at":"2026-05-13T21:03:19.923664Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"cited_work":{"arxiv_id":"2506.14142","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14142","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mllm-as-a-judge: Assessing multimodal llm-as-a-judge with vision- language benchmark","venue":null,"work_id":"ebcfc1db-1baa-4c66-b424-458bd1210741","year":2025},"citing_paper":{"arxiv_id":"2604.12144","last_updated":"2026-07-01T22:34:57Z","snapshot_observed_at":"2026-08-12T14:41:56.904894Z","submitted_at":"2026-04-13T23:48:35Z","title":"VERITAS: A Multi-Agent Co-Scientist for Verifiable Image-Derived Hypothesis Testing","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T14:56:06.372343Z"},"links":{"cited_paper":"/paper/2506.14142","citing_paper":"/paper/2604.12144"},"observation_digest":"sha256:cdc87963c4ef80a6c80fb9a094ed539477b7b2a498a6392225c568c7edad9f4f","observation_id":"6a5c0a15-e478-4c00-b518-b1ab146edd6f","resolution":{"observed_at":"2026-05-11T11:26:02.072121Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.14142","snapshot_observed_at":"2026-07-14T06:30:16.612345Z","title":"Radfabric: Agentic ai system with reasoning capability for radiology.arXiv preprint arXiv:2506.14142, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.11175","last_updated":"2026-07-13T07:16:50Z","snapshot_observed_at":"2026-07-16T23:19:14.481825Z","submitted_at":"2026-07-13T07:16:50Z","title":"The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-14T06:30:16.612345Z"},"links":{"cited_paper":"/paper/2506.14142","citing_paper":"/paper/2607.11175"},"observation_digest":"sha256:25abd3e5ed1ab2dff54e79c17de29f70ff18389dc4f99cf4b519e24e69d6233c","observation_id":"a4695557-b46d-4833-a1b7-7573700dfae8","resolution":{"observed_at":"2026-07-14T06:30:16.612345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.14142/citation-record","integrity":"/paper/2506.14142/integrity","json":"/paper/2506.14142/citation-record.json","paper":"/paper/2506.14142"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:24:26.886334Z","title":"Unichest: Conquer-and-divide pre-training for multi-source chest x-ray classification,","venue":null,"work_id":"06906d65-6460-4dd2-87fd-eb9a54aef930","year":2024},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:24.911056Z"},"links":{"citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:a61d8ba63c28c9a6728e6299aeaae5917add0d361243094fa74208c86c1b602e","observation_id":"d5a90d4d-29ee-466f-b832-fad5a649821d","resolution":{"observed_at":"2026-08-07T00:24:26.960927Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T00:24:26.697526Z","title":"Torchxrayvision: A library of chest x-ray datasets and models,","venue":null,"work_id":"b59236cc-c398-4032-a1ec-54eeadd8392b","year":2022},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.016318Z"},"links":{"citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:55eb018eebf90084b984a97bb2e4691d34edfef6e354d6b07f2806e208efb908","observation_id":"684eced7-52cc-4839-a971-20ae0dc50c0a","resolution":{"observed_at":"2026-08-07T00:24:26.798742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T00:24:26.499623Z","title":"Robust stochastic gradient descent with momentum based framework for enhanced chest x-ray image diagnosis,","venue":null,"work_id":"d01b86a2-9a8c-49dc-92ec-85dc091009b9","year":2024},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.091299Z"},"links":{"citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:4517ad1df7ac5f610f630197fd41b41daceb33e5121d78164a1fd38b6f2792be","observation_id":"c415e550-4c9d-49d3-94f9-374b93045fa1","resolution":{"observed_at":"2026-08-07T00:24:26.555342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05225","last_updated":"2017-12-25T11:09:06Z","snapshot_observed_at":"2026-08-06T22:13:27.249372Z","submitted_at":"2017-11-14T17:58:50Z","title":"CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05225","snapshot_observed_at":"2026-08-07T00:24:25.171891Z","title":"Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.171891Z"},"links":{"cited_paper":"/paper/1711.05225","citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:67e3910cd1ed4e3215f39c4b8424ee45686dd5184ebba6f34486399ef8b6783e","observation_id":"897bed55-c825-4789-aeca-5b35c6a05066","resolution":{"observed_at":"2026-08-07T00:24:25.171891Z","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":"2026-08-07T00:24:26.335622Z","title":"Grad-cam: Visual expla- nations from deep networks via gradient-based localization,","venue":null,"work_id":"e28073bb-2861-4645-92c1-560ea0eb73a6","year":2017},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.258082Z"},"links":{"citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:342a1ba6fa5f916356b2a89631f4543dd7e1ee438781250e1f4d91de0c456ff2","observation_id":"fa9454aa-285f-4341-8de8-c9700e98491c","resolution":{"observed_at":"2026-08-07T00:24:26.427580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T00:24:26.140850Z","title":"Chexagent: Towards a foundation model for chest x-ray interpretation,","venue":null,"work_id":"e8f3f72f-d880-43ee-bbf0-54773480a65b","year":2024},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.352033Z"},"links":{"citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:57505d0702b278e843fc02973483a717734e46b6966a971f42621b4acb91e6ed","observation_id":"1323e6a0-27c6-4b27-a30f-fd50eabcfa8e","resolution":{"observed_at":"2026-08-07T00:24:26.237835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-08-12T17:29:41.806995Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-08-07T00:24:25.480772Z","title":"Qwen2.5-vl technical report,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.480772Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:4a08f82454f780beaffab94b1adf0e7d48eb0e5704e4f6a98322c375fe3f33be","observation_id":"d6d66597-8945-4341-a36c-7dd61f7d0033","resolution":{"observed_at":"2026-08-07T00:24:25.480772Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-08-07T00:24:25.556253Z","title":"Openai o1 system card,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.556253Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:94f2b56cfcfd18a827ff69b70721fc77e1cd20d6b062f0e2c12449f1ef42aa11","observation_id":"89301da7-ed0e-43a9-b4aa-1131b6c93a54","resolution":{"observed_at":"2026-08-07T00:24:25.556253Z","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":"2026-08-07T00:24:25.959175Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning,","venue":null,"work_id":"19990d93-f9db-4072-b207-e2ddd3f5a0be","year":null},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.658536Z"},"links":{"citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:8cebf12ce33f49a8b581da1f91d347f0c39074f12d8bef2989fb00e5f98a881b","observation_id":"013f06be-2ca1-4eec-a43e-936e833d04e8","resolution":{"observed_at":"2026-08-07T00:24:26.044064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2026-08-07T00:24:25.735607Z","title":"Available: https://arxiv.org/abs/2501.12948 14","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T00:24:25.735607Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2506.14142"},"observation_digest":"sha256:67c40f47116ae6890169cc5244af67fb043fc78829af1b5c4f6edcf6d7f97c5f","observation_id":"9b2d6cba-2dc8-47b4-bd07-dec9324f181c","resolution":{"observed_at":"2026-08-07T00:24:25.735607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.14142","last_updated":"2025-06-17T03:10:33Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T13:19:17.739506Z","submitted_at":"2025-06-17T03:10:33Z","title":"RadFabric: Agentic AI System with Reasoning Capability for Radiology"},"reference_resolution":{"displayed":10,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":6},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 4 inbound Pith citation observations for arXiv:2506.14142."}