{"as_of":"2026-08-17T16:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f9f81c086e801fe745eb81d6ce2b02eec293d6ee9b94a6c6ab2722a46fd593f4","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T22:30:32.077491Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"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/2508.09205/citation-record","integrity":"/paper/2508.09205/integrity","json":"/paper/2508.09205/citation-record.json","paper":"/paper/2508.09205"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1056/nejm199907223410407","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Magnetic Resonance Cholangiopancreatography","venue":"New England Journal of Medicine","work_id":"5f46d68e-ceec-45cb-b1a3-20cac726ddd8","year":1999},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.891352Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:2f9896b539fe0dd3048d4b628ed84b4866a85ad614b4404bd86548af0caf5796","observation_id":"f4a2f030-2840-4973-a10c-85ffe85ea248","resolution":{"observed_at":"2026-08-05T22:30:32.549577Z","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":"10.1148/radiographics.19.1.g99ja0525","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"MR Cholangiography: Technical Advances and Clinical Applications","venue":"Radiographics","work_id":"d17c6220-9144-4167-bab8-f313614cdff8","year":1999},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.896174Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:c7fd119f8b57cbdd16e8e72c90d4b8aad7cc430404118907737170dba0de562c","observation_id":"42cad1d8-f321-403a-8206-13497f03d7fe","resolution":{"observed_at":"2026-08-05T22:30:32.538729Z","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":"10.3310/hta8100","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"A systematic review and economic evaluation of magnetic resonance cholangiopancreatography compared with diagnostic endoscopic retrograde cholangiopancreatography","venue":"Health Technology Assessment","work_id":"66d643b1-48b1-49ca-be45-53fb6535688e","year":2004},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.900282Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:344be70139278368c95c24699c8959fc31e6bca834fcc9908c3319a559c8146e","observation_id":"2357fb9e-c4fd-447b-8ca9-5b06b8a5295e","resolution":{"observed_at":"2026-08-05T22:30:32.527657Z","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":"10.1148/radiology.206.2.9457189","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Optimal MR cholangiopancreatographic sequence and its clinical application","venue":"Radiology","work_id":"748e3f15-7418-4de8-814f-f7bce689eaf6","year":1998},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.903943Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:68fb168038c72735cd36879de0411aac7762812a331f76fe8143230acff2c5c2","observation_id":"265b6194-d7b8-417d-8649-cd42786e0ea2","resolution":{"observed_at":"2026-08-05T22:30:32.513029Z","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":"10.1097/rct.0b013e3181852193","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Journal of Computer Assisted Tomography","work_id":"a494f842-6a1d-4aba-9105-4ba2652085f5","year":2009},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.908637Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:bef6303a2382ad3cda80956f2a6ae9dc18492fb26e3b4b9ee9df5f05368625fa","observation_id":"46aef30b-fc6a-4cea-b956-b7e17dc117da","resolution":{"observed_at":"2026-08-05T22:30:32.500923Z","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":"10.1002/jmri.24033","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Usefulness of the SPACE pulse sequence at 1.5T MR cholangiography: Comparison of image quality and image acquisition time with conventional 3D��TSE sequence","venue":"Journal of Magnetic Resonance Imaging","work_id":"39f8df63-6bae-4a4b-b22d-03376b6c2102","year":2013},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.913015Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:a2921d4ddca20a27d5131fb1a85296ef2f6f040ff6a1b27359cbc974eb5fe9f7","observation_id":"b0f77c7f-f164-43a8-84a3-90156008a274","resolution":{"observed_at":"2026-08-05T22:30:32.488816Z","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":"10.1007/s00261-016-0936-z","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"3D T2-weighted and Gd-EOB-DTPA-enhanced 3D T1-weighted MR cholangiography for evaluation of biliary anatomy in living liver donors","venue":"Abdominal Radiology","work_id":"00e1f159-25e7-407c-a31f-40f9cfe6f3de","year":2017},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.917219Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:695f8b5cd0a4e17abff83b0cff4acbf8a1aead681b6aa227398d071ef4735c68","observation_id":"40a392f5-eae5-4d08-9f56-8d607e5a0548","resolution":{"observed_at":"2026-08-05T22:30:32.477119Z","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":"10.1097/rli.0000000000000380","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Clinical Feasibility of 3-Dimensional Magnetic Resonance Cholangiopancreatography Using Compressed Sensing: Comparison of Image Quality and Diagnostic Performance","venue":"Investigative Radiology","work_id":"b98cb684-9a57-4a4a-851e-a6b230dff5a4","year":2017},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.921230Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:aae60c7834d9ccd8a2f07499b8f9d5f1cd81e4785ae84ab2450ad49e9dbbee50","observation_id":"f58fc854-acee-4a26-982c-2913f0ece276","resolution":{"observed_at":"2026-08-05T22:30:32.464946Z","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":"10.1002/jmri.21485","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Navigator��triggered prospective acquisition correction (PACE) technique vs","venue":"Journal of Magnetic Resonance Imaging","work_id":"108c4784-97c0-4944-9739-bde7a10a3be7","year":2008},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.925019Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:dd240da5276a4e49211b52783f3b2b97a199ace2ce7f5d0f847cb17793cc5ce2","observation_id":"3ccd6fd4-6453-4017-a509-9dca70dab395","resolution":{"observed_at":"2026-08-05T22:30:32.452738Z","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":"2026-08-05T22:30:32.983516Z","title":"Breath-held MR Cholangiopancreatography (MRCP) using a 3D Dixon fat–water separated balanced steady state free precession sequence","venue":null,"work_id":"c92649c4-c3ed-4da0-b78b-6dff15ee829a","year":2013},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.928817Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:098d328b072b6d275e6a9ca785e98ecf22e9e762076249a154a76cc9dbbd76ee","observation_id":"f742335c-900f-4399-b5b8-e45b1bd56151","resolution":{"observed_at":"2026-08-05T22:30:32.987942Z","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":"10.1259/bjr.20130036","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"MR cholangiopancreatography at 3.0 T in children: diagnostic quality and ability in assessment of common paediatric pancreatobiliary pathology","venue":"British Journal of Radiology","work_id":"cf612983-692b-423d-b5d9-ec8a3bd0dad8","year":2013},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.936522Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:f33ac730842488abbdba05d36f4f1959a3cc00360833686dd3639181a9344c5c","observation_id":"e72d5cb4-287d-4f37-88a6-3b44f43bdf27","resolution":{"observed_at":"2026-08-05T22:30:32.428591Z","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":"10.1148/radiol.2493080389","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Possible Biliary Disease: Diagnostic Performance of High-Spatial-Resolution Isotropic 3D T2-weighted MRCP","venue":"Radiology","work_id":"61910730-88b7-492e-aadc-c4938a72e3c4","year":2008},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.940110Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:a97605e5a89a40523ce27230b2b5705026a992c9ab398945d54197f6086fbe7c","observation_id":"09f3300f-4aa5-4802-b778-a6127e194eaf","resolution":{"observed_at":"2026-08-05T22:30:32.416102Z","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":"10.1007/s00330-018-5550-8","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Breath-holding 3D MRCP: the time is now? ��������������������","venue":"European Radiology","work_id":"994e76f9-94ae-4703-be91-e5e64adce518","year":2018},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.943400Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:0f551f9662200181f9ff0a175bf6c6604a78c7da9d5f9915d729b7a1e34a809b","observation_id":"e78b51bf-570d-4b8d-8597-067a1a4a3e05","resolution":{"observed_at":"2026-08-05T22:30:32.402475Z","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":"10.1007/s00330-017-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.385661Z","title":"Magnetic resonance cholangiopancreatography with GRASE sequence at 3.0T: does it improve image quality and acquisition time as compared with 3D TSE? ��������������������","venue":null,"work_id":"3c9ca9e4-a8bd-4bce-bc0d-46934d52bc14","year":2018},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.951077Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:94bc4b5c06f1299da85e0c81f205b4dcd7c02c95c508045c365af0d692a57315","observation_id":"cb60e593-6632-4f77-8fba-229ebe8a1a00","resolution":{"observed_at":"2026-08-05T22:30:32.389508Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"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":"2026-08-05T22:30:32.970340Z","title":"Rapid 3D navigator-triggered MR cholangiopancreatography with SPACE sequence at 3T: only one-third acquisition time of conventional 3D SPACE navigator-triggered MRCP","venue":null,"work_id":"197b5684-ae95-40c4-8465-4f5abf5ce347","year":2020},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.954492Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:13143c6629d8f26e9d18c433d6b93c85fd9b993887e0596007449c26711eb5a6","observation_id":"440619bf-509d-4d8a-b1d5-3f98e8786347","resolution":{"observed_at":"2026-08-05T22:30:32.974125Z","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":"10.1148/radiol.2016151935","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Three-dimensional MR Cholangiopancreatography in a Breath Hold with Sparsity-based Reconstruction of Highly Undersampled Data","venue":"Radiology","work_id":"f4f93a66-aa85-4b64-baab-03b0630c09ea","year":2016},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.962167Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:666adf20042c7d019d23b4e5f0f8aebfcb6d4484560b2d8954a828c8c63aadae","observation_id":"68525ac0-1e56-4a4e-abcc-fad3687d5705","resolution":{"observed_at":"2026-08-05T22:30:32.363496Z","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":"10.1097/rli.0000000000000421","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Compressed-Sensing Accelerated 3-Dimensional Magnetic Resonance Cholangiopancreatography: Application in Suspected Pancreatic Diseases","venue":"Investigative Radiology","work_id":"01129503-7bb4-4413-8d80-addaa59de580","year":2018},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.965351Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:ce0691c484a40c7402dca81e7e51fd2b7b792bdbeee927c369a0df1b4f964b61","observation_id":"cd6063e4-9419-45c6-8eb4-5c18076e085b","resolution":{"observed_at":"2026-08-05T22:30:32.350766Z","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":"10.1002/jmri.26049","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":null,"venue":"Journal of Magnetic Resonance Imaging","work_id":"40a6b04e-1b77-4afe-bba2-e45ba6eaa9b7","year":2018},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.969668Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:e8cc010b6ea57ee82673a9472d1f4ce9a456fbc2aa214be482facf016fbaa0f5","observation_id":"d63d7734-7515-4ff0-b39d-a185c5dba342","resolution":{"observed_at":"2026-08-05T22:30:32.338866Z","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":"10.1016/j.mri.2017.09.014","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Patient-adapted respiratory training: Effect on navigator-triggered 3D MRCP in painful pancreatobiliary disorders","venue":"Magnetic Resonance Imaging","work_id":"be7e046f-9bb1-4ada-83ee-d1929b5a690c","year":2018},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.974063Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:2aed2d00ca37263b4d59cc9a4ff608a3c5d3119aad3b637c853dd8b26313c03e","observation_id":"05fd8580-c2d6-4b98-a848-857891206e8b","resolution":{"observed_at":"2026-08-05T22:30:32.325667Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:31.978353Z","title":"Sparse MRI: The application of compressed sensing for rapid MR imaging","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.978353Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:bc1a4a3ffd02bbdbbdfc7bd4060dbe7fc5d5cccd602871cdcbd9ed205370ad3b","observation_id":"5c1fa9a3-2ef2-4ba6-8067-251b77b7c873","resolution":{"observed_at":"2026-08-05T22:30:31.978353Z","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":"10.1007/s00330-005-2795-9","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Assessment of reproducibility and stability of different breath-hold maneuvres by dynamic MRI: comparison between healthy adults 23 and patients with pulmonary hypertension","venue":"European Radiology","work_id":"a1b2fd5b-44f7-4e00-9d3a-3b7af0a02cf0","year":2006},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.982154Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:ba73fc7e57354812fd85a91110e2b8293a40c7c270e42c4690235b70ecb6c1a2","observation_id":"f4379859-99b5-4f14-89d3-24ce8d85a685","resolution":{"observed_at":"2026-08-05T22:30:32.304224Z","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":"10.1186/s12968-020-00642-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Breath-hold and free-breathing quantitative assessment of biventricular volume and function using compressed SENSE: a clinical validation in children and young adults","venue":"Journal of Cardiovascular Magnetic Resonance","work_id":"f79775fd-7488-4ef3-b2fd-b743da7a5127","year":2020},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.985989Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:5e0302ba0b054376dd3ab4a8c0aa821d97fdb180af010a274186df9fb79bc732","observation_id":"a0c61356-a208-438a-8487-6bd1452d1faa","resolution":{"observed_at":"2026-08-05T22:30:32.292015Z","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":"10.1002/mrm.22463","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI","venue":"Magnetic Resonance in Medicine","work_id":"64238404-fb7b-4dd6-8e4e-afee561471d3","year":2010},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.989601Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:2dcb4b3034b886fa1e7e32272dbe73d3b4a9d51ff4a514af95b8486f6ff47075","observation_id":"38983a36-d5bf-4eef-a72d-dcfce589b423","resolution":{"observed_at":"2026-08-05T22:30:32.279839Z","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":"10.1002/mrm.25702","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Accelerated T1ρ acquisition for knee cartilage quantification using compressed sensing and data-driven parallel imaging: A feasibility study","venue":"Magnetic Resonance in Medicine","work_id":"5093c612-b261-4d56-8e17-2d9266ed9c6f","year":2016},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.993024Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:18ac3d001170783773cad00069b5df5db6837f7b1de7c2f384bc3c405208e075","observation_id":"ebea95c9-4b9c-4d9c-9329-033f557e336c","resolution":{"observed_at":"2026-08-05T22:30:32.267281Z","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":"2018.28653","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.862739Z","title":"MoDL: Model-Based Deep Learning Architecture for Inverse Problems","venue":null,"work_id":"b8c1a284-7ca7-49ac-851b-06ffec20f276","year":2019},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.996984Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:40f477212a2d130e88351466d8c78a00d152e519979d7b33cff1de2d67788464","observation_id":"c544eab1-38ba-44f2-af00-921aaa0dd03d","resolution":{"observed_at":"2026-08-05T22:30:32.869589Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"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":"10.1002/nbm.70002","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Deep Learning��Based Accelerated MR Cholangiopancreatography Without Fully��Sampled Data","venue":"NMR in Biomedicine","work_id":"26b47a91-bafb-4b5d-b0da-5e092139f52e","year":2025},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.000542Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:cba28239a6ba2922e6fed201f3adb0cc383650a7be853af51cb78b1cff9181e2","observation_id":"001ff4f0-d5fb-4490-8656-d55da22fd35e","resolution":{"observed_at":"2026-08-05T22:30:32.254229Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.004935Z","title":"Self��supervised learning of physics��guided reconstruction neural networks without fully sampled reference data","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.004935Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:d092ce1bbf5b779770074cb2df77db9874b12010decd595c0dc65c14cf01255e","observation_id":"a22a90a1-9b25-4eaf-9688-3471b7d9e47c","resolution":{"observed_at":"2026-08-05T22:30:32.004935Z","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":"2026-08-05T22:30:32.958428Z","title":"Zero-Shot Self-Supervised Learning for MRI Reconstruction","venue":null,"work_id":"acfdb81a-b94e-436a-95c1-d8bcf59eecb7","year":2022},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.008942Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:5311bd46f7a2f6cf22a50467ac75e9998458d32b64ae4af2c595b08e60d90d25","observation_id":"9c3f5138-4e8f-48b2-b213-618f6edaf559","resolution":{"observed_at":"2026-08-05T22:30:32.962096Z","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":"10.1002/mrm.27420","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Scan��specific robust artificial��neural�� networks for k��space interpolation (RAKI) reconstruction: Database��free deep learning for fast imaging","venue":"Magnetic Resonance in Medicine","work_id":"fb09d6c9-6519-48a7-9811-51e1fe899ae0","year":2019},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.012406Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:107b4fb88529029646223ed28c53da1ee022a996d295c1766c77a96313cb508d","observation_id":"0cc7fe37-2223-4cc8-8796-5ef52e9a6c9b","resolution":{"observed_at":"2026-08-05T22:30:32.231594Z","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":"2022.11924","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.779590Z","title":"Residual RAKI: A hybrid linear and non-linear approach for scan-specific k-space deep learning","venue":null,"work_id":"995a1b68-a8c3-4772-86e1-4eebf8808914","year":2022},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.015805Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:3b0a6a0e87645103270236760a6f949ddb32fb75ce70f7217d3dbca056fa0fec","observation_id":"0b20af58-d399-429b-ba48-39c846dffefc","resolution":{"observed_at":"2026-08-05T22:30:32.786736Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.019378Z","title":"Deep Image Prior","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.019378Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:7c03a3e5a324231e6bbd1a21b6a9e5bd351395d6ca58cbd7f3b19f47f14db8fc","observation_id":"45276e33-439f-44ad-b9e9-775d1823e5d9","resolution":{"observed_at":"2026-08-05T22:30:32.019378Z","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":"2026-08-05T22:30:32.946275Z","title":"Implicit neural representations with periodic activation functions","venue":null,"work_id":"5988312d-8481-47a9-830c-0c035d23ccb6","year":2020},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.023168Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:c6007fa7bef7a4cd046d3bfad2ba8c941aeb8a466ab241eed8413e686a11c9a9","observation_id":"6b00da95-b851-4c6a-9633-9a019f07871b","resolution":{"observed_at":"2026-08-05T22:30:32.950326Z","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":"2026-08-05T22:30:32.934219Z","title":"Improved Multi-shot Diffusion-Weighted MRI with Zero-Shot Self-supervised Learning Reconstruction","venue":null,"work_id":"9052b468-fea1-4e95-adf8-c522b62f0ba6","year":2023},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.026592Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:9424fdf82a59776fa9e0a845707a82d12601cc58e80ee0cb5b85ad86060cf889","observation_id":"01901d0b-9c82-44c7-840e-5ebc5b6e7fbf","resolution":{"observed_at":"2026-08-05T22:30:32.938272Z","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":"5880.92346","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.630724Z","title":null,"venue":null,"work_id":"52826375-a9ff-4348-b813-8dd0db099c3d","year":2005},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.034151Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:66c6d682b06d295a3dce579e11af9e58dd6cd8e8657bf86e2a1525cc2e308e07","observation_id":"c4152981-2329-4d08-9db1-df87d279bf53","resolution":{"observed_at":"2026-08-05T22:30:32.636317Z","resolver_source":"raw_fallback","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.038231Z","title":"ISMRM Raw data format: A proposed standard for MRI raw datasets","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.038231Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:c02b396384ce1a38f2b6c2481b4d96752430d3ae7052b05a2190c852b7826c9a","observation_id":"15b9e547-300a-4cd9-a395-a219f1a809ee","resolution":{"observed_at":"2026-08-05T22:30:32.038231Z","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":"2026-08-05T22:30:32.920767Z","title":"Python port of mapVBVD","venue":null,"work_id":"b947544a-af55-400e-a41f-9b5924bcc8aa","year":2025},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.042395Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:a7295a0e78730d9e97f6de3aa73421241a67813afb2c7888990607c9d4d6ade1","observation_id":"8efc26d6-6ad2-4310-9f95-31e19f26f798","resolution":{"observed_at":"2026-08-05T22:30:32.924519Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.046808Z","title":"ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.046808Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:8d9f51cc865ffafbf078e59949461a6c310136ba510c05d96e703107961e35df","observation_id":"371bcee8-9f71-4641-868e-10e4c0083efc","resolution":{"observed_at":"2026-08-05T22:30:32.046808Z","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":"2026-08-05T22:30:32.906772Z","title":"SigPy: A Python Package for High Performance Iterative Reconstruction","venue":null,"work_id":"0ae9d575-5330-4d11-aa95-4b52a325f170","year":2019},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.050728Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:8c422711ebef73a41c86a7799eba838b34f5d91ed10eaed9111a86b6c7a3f941","observation_id":"909a2be4-04f1-46a5-acf4-65cb62a683fc","resolution":{"observed_at":"2026-08-05T22:30:32.911228Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:30:32.054663Z","title":"Deep Residual Learning for Image Recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.054663Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:bbd5bdf115bc944d578905289541d35d37647a969aeb5d6dd922730ba8cde659","observation_id":"cdbfe65f-d01a-4782-80ab-cb5cd3d1c7e9","resolution":{"observed_at":"2026-08-05T22:30:32.054663Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1608.03983","last_updated":"2017-05-03T16:28:09Z","snapshot_observed_at":"2026-07-06T05:06:55.589962Z","submitted_at":"2016-08-13T13:46:05Z","title":"SGDR: Stochastic Gradient Descent with Warm Restarts","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.03983","snapshot_observed_at":"2026-08-05T22:30:32.058198Z","title":"SGDR: STOCHASTIC GRADIENT DESCENT WITH WARM RESTARTS","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.058198Z"},"links":{"cited_paper":"/paper/1608.03983","citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:7405bb82b22ce7721c5cc6d364c10c01ee2121870933005f5e6292f30a5ea701","observation_id":"7dbe019d-7015-4ef9-996f-fb4cd3aa59dd","resolution":{"observed_at":"2026-08-05T22:30:32.058198Z","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":"2026-08-05T22:30:32.062407Z","title":"Generalized autocalibrating partially parallel acquisitions (GRAPPA)","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.062407Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:da243d1a1cdb5d47ed7cc173fba2176e8f66193ca9cf56b8d15e1829af0dfc01","observation_id":"35cc1645-3995-4a51-94d3-f3cc8c923131","resolution":{"observed_at":"2026-08-05T22:30:32.062407Z","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":"2026-08-05T22:30:32.893448Z","title":"Python implementations of GRAPPA-like algorithms","venue":null,"work_id":"31d58561-f367-4b4f-83e6-202d30081567","year":null},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.065807Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:14762881f3ae63d97a33a7d1c4b6ad2eb16037a7385ba7cf7ed43664d3a164bd","observation_id":"62473bf7-3aba-4239-b956-c02793fb2963","resolution":{"observed_at":"2026-08-05T22:30:32.897512Z","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":"10.1111/jan.12351","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Patients’ experiences in magnetic resonance imaging (MRI) and their experiences of breath holding techniques","venue":"Journal of Advanced Nursing","work_id":"c42ae6db-4588-4947-8a46-2b866d2516f3","year":2014},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.073546Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:7239c972be55e001610d051fdb11850da795d7fbc0167aba1f5146219af1e370","observation_id":"e1c4daf7-2124-4cf0-9772-9df1b70497f7","resolution":{"observed_at":"2026-08-05T22:30:32.141114Z","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":"10.1002/mrm.29100","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Robust partial Fourier reconstruction for diffusion��weighted imaging using a recurrent convolutional neural network","venue":"arXiv (Cornell University)","work_id":"fb9ec541-9e7c-458a-959b-5a850aff5930","year":2022},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.077491Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:100302481f09dab9bab063e7a4bb820c72f90324eb60dc18c022d8118e7dc204","observation_id":"bf092763-6973-4a34-9f8f-d45241cf4f7d","resolution":{"observed_at":"2026-08-05T22:30:32.110983Z","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":"10.1007/s00261-019-02342-3","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Abdominal Radiology","work_id":"57d50abb-863c-46c6-817b-1529ac2bc495","year":null},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":140,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.957741Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:94fe1ba3c07a9d2d723eedea89b94050dcc4d22a6f4c321082f295b1ece1620a","observation_id":"7ff45686-c974-48af-8499-951d269cfcb2","resolution":{"observed_at":"2026-08-05T22:30:32.376503Z","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":"10.1007/978-3-031-43907-0_44","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":null,"venue":"Lecture notes in computer science","work_id":"7c7b45d0-106e-495f-8333-6deeeca26010","year":null},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":466,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.030374Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:63f464fb045531dbd9f60a83008fecf44f27bfc39f3b55b5b5837e89bdfc10e1","observation_id":"e012821f-3ef5-4025-96b2-a1b18e9c0149","resolution":{"observed_at":"2026-08-05T22:30:32.217922Z","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":"10.1016/j.mri.2013.06.008","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Magnetic Resonance Imaging","work_id":"33e4228c-fdba-497b-b4ff-5e0182940aa7","year":2013},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":1270,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:31.932685Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:29a415e150362c6a480da9ddb7418046feb66c5b837b5720902ad93419cd3591","observation_id":"87f98850-3f76-4f30-be6f-7d92999c5d32","resolution":{"observed_at":"2026-08-05T22:30:32.440827Z","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":"2026-08-05T22:30:32.879617Z","title":null,"venue":null,"work_id":"d03e88f9-7712-4f2b-af3e-50f82faa634b","year":null},"citing_paper":{"arxiv_id":"2508.09205","last_updated":"2025-08-15T02:45:28Z","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-05T22:30:32.069257Z"},"links":{"citing_paper":"/paper/2508.09205"},"observation_digest":"sha256:e017156d381f531134a9059441a53e4f6d6fdde035ec337e2c64905a98df3baf","observation_id":"0a009d1e-890a-4a11-80fe-5ffdeadcd01b","resolution":{"observed_at":"2026-08-05T22:30:32.883818Z","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":"2508.09205","last_updated":"2025-08-15T02:45:28Z","latest_version":2,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-05T22:30:27.306408Z","submitted_at":"2025-08-09T10:06:15Z","title":"From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":1,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":9,"verified_exact":28,"verified_fuzzy":8},"total_outbound_references":48},"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 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2508.09205."}