{"as_of":"2026-08-08T01:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:002227b154133880d6c9f6654cfa16bcc2c3e7c837a88d2af21a9ec4b7057f35","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":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:26:34.941345Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":431,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-07T14:26:34.941345Z","title":"D’Amour et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.18893","last_updated":"2025-05-30T14:09:51Z","snapshot_observed_at":"2026-08-07T14:21:37.953874Z","submitted_at":"2025-05-24T22:35:32Z","title":"Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects","version":4},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:26:34.941345Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2505.18893"},"observation_digest":"sha256:156aa3c51a06d38d939acd74d58404d22333e872cbaac2ae846e1e253efe50c4","observation_id":"3dbf9447-7d0d-4ac6-90fd-f2d82493a473","resolution":{"observed_at":"2026-08-07T14:26:34.941345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-07T12:11:20.859619Z","title":"Under- specification presents challenges for credibility in modern machine learning.arXiv preprint arXiv:2011.03395, 2020","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2506.00407","last_updated":"2025-05-31T05:54:49Z","snapshot_observed_at":"2026-08-07T12:03:48.254921Z","submitted_at":"2025-05-31T05:54:49Z","title":"Bias as a Virtue: Rethinking Generalization under Distribution Shifts","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T12:11:20.859619Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2506.00407"},"observation_digest":"sha256:759b7bec67653481652c6c5f44707b75570fb530fdfb201783762b4ea6a71f53","observation_id":"44cc8bec-fded-441a-91a3-7bfeebf55772","resolution":{"observed_at":"2026-08-07T12:11:20.859619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-06T19:45:34.515443Z","title":"D., et al","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.04788","last_updated":"2025-07-07T09:09:52Z","snapshot_observed_at":"2026-08-06T22:46:57.461768Z","submitted_at":"2025-07-07T09:09:52Z","title":"Machine Learning from Explanations","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T19:45:34.515443Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2507.04788"},"observation_digest":"sha256:b163d253660cdd281a47397ef8d935cd71fc96bdf743383d2beb937204129958","observation_id":"f97dfb09-2fc6-40d3-a144-7ddbd9701bf3","resolution":{"observed_at":"2026-08-06T19:45:34.515443Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2604.08192","last_updated":"2026-04-09T12:44:19Z","snapshot_observed_at":"2026-07-06T22:57:22.475588Z","submitted_at":"2026-04-09T12:44:19Z","title":"Inside-Out: Measuring Generalization in Vision Transformers Through Inner Workings","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T18:28:49.855280Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2604.08192"},"observation_digest":"sha256:3e0addc2ed22b573695fc0ff43dcde20e16e0806b1b61d97ca3740b975606bc3","observation_id":"ac7d3d50-4077-4eac-af03-ba2c18e903c5","resolution":{"observed_at":"2026-05-11T00:30:54.271248Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2605.04905","last_updated":"2026-05-12T09:55:21Z","snapshot_observed_at":"2026-08-02T09:21:46.362871Z","submitted_at":"2026-05-06T13:35:04Z","title":"Cross-Model Consistency of Feature Importance in Electrospinning: Separating Robust from Model-Dependent Features","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T18:34:30.059723Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2605.04905"},"observation_digest":"sha256:80ccceb7e64144bc674fe85321ec5020176d699f7adafebe41d211186e11adc9","observation_id":"30c166a0-cf41-4ee9-a0ea-79c961501dd1","resolution":{"observed_at":"2026-05-09T06:20:41.902028Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2605.04905","last_updated":"2026-05-12T09:55:21Z","snapshot_observed_at":"2026-08-02T09:21:46.362871Z","submitted_at":"2026-05-06T13:35:04Z","title":"Cross-Model Consistency of Feature Importance in Electrospinning: Separating Robust from Model-Dependent Features","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-13T07:01:43.144828Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2605.04905"},"observation_digest":"sha256:8f9dad8451035510023f259c0183cd28b21cd22e11426a5c24aaca5b0e341ebc","observation_id":"f1a75c7b-a5c9-43ad-b81f-742d5a5a1bd2","resolution":{"observed_at":"2026-05-13T07:02:27.187164Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2605.13826","last_updated":"2026-05-13T17:50:57Z","snapshot_observed_at":"2026-07-06T23:25:21.032938Z","submitted_at":"2026-05-13T17:50:57Z","title":"Reducing cross-sample prediction churn in scientific machine learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-14T19:15:12.498704Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2605.13826"},"observation_digest":"sha256:68d973303ca12280d1ff9b4e76e7301b3815ba5823d8fa33df7e2999408af72a","observation_id":"5afa3c22-c07b-41cf-81c7-d38912b9d84c","resolution":{"observed_at":"2026-05-14T19:17:50.858639Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2605.15183","last_updated":"2026-05-14T17:58:27Z","snapshot_observed_at":"2026-07-06T23:26:32.979566Z","submitted_at":"2026-05-14T17:58:27Z","title":"When Are Two Networks the Same? Tensor Similarity for Mechanistic Interpretability","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-15T03:17:22.217041Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2605.15183"},"observation_digest":"sha256:23a3cf814810bf34d47dd28793e2569094c7b37f51ee8df2d124ab867e3ddc6b","observation_id":"d3d1b960-003c-455e-8cef-a8fb8c27f23f","resolution":{"observed_at":"2026-05-15T03:19:43.678255Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2606.09881","last_updated":"2026-06-03T05:44:29Z","snapshot_observed_at":"2026-07-06T23:49:08.412079Z","submitted_at":"2026-06-03T05:44:29Z","title":"Toward Calibrated, Fair, and accurate Deepfake Detection","version":1},"reference_index":121,"source":"arxiv_source","source_observed_at":"2026-06-28T07:05:18.026601Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2606.09881"},"observation_digest":"sha256:b3773ad7a2b95b8349de72a5fcf4e32d188ba85b2eb1e131f43b0cf4c07b528a","observation_id":"8d859746-924f-4441-96a1-0bf261bbaaa4","resolution":{"observed_at":"2026-06-28T07:11:45.378289Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2606.12277","last_updated":"2026-06-10T16:17:48Z","snapshot_observed_at":"2026-08-07T18:10:45.483146Z","submitted_at":"2026-06-10T16:17:48Z","title":"Finding Multiple Interpretations in Datasets","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T10:08:31.702401Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2606.12277"},"observation_digest":"sha256:4a99a754f91706bbc23aa3b29a911d468fb828ee89e328a13376479194c09508","observation_id":"fb496ce3-1f07-4ebe-a8e4-c5d7c32dc49b","resolution":{"observed_at":"2026-07-03T10:17:57.687582Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2606.17582","last_updated":"2026-06-16T06:43:46Z","snapshot_observed_at":"2026-08-07T16:07:11.624751Z","submitted_at":"2026-06-16T06:43:46Z","title":"Collaborative Large and Small Language Models for Accurate and Scalable Data Repair","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-26T22:25:39.533017Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2606.17582"},"observation_digest":"sha256:3ba45faa34fee873170dd0f01dca77826b4189627a2599916e3bf0f6040f6208","observation_id":"dfd22c7c-1565-403d-9ea7-c35dada4d08d","resolution":{"observed_at":"2026-07-03T23:19:04.264397Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning","version":2},"cited_work":{"arxiv_id":"2011.03395","doi":"10.48550/arxiv.2011.03395","metadata_source":"arxiv_reference","pith_arxiv_id":"2011.03395","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ISBN 9781510838819","venue":"arXiv (Cornell University)","work_id":"eec6624e-eacc-4bb2-9a7f-5fafded81041","year":2020},"citing_paper":{"arxiv_id":"2606.31589","last_updated":"2026-06-30T12:41:16Z","snapshot_observed_at":"2026-08-01T11:13:54.408482Z","submitted_at":"2026-06-30T12:41:16Z","title":"From Failure to Alignment: A Requirements Engineering Framework for Machine Learning Systems","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-01T04:36:40.883797Z"},"links":{"cited_paper":"/paper/2011.03395","citing_paper":"/paper/2606.31589"},"observation_digest":"sha256:9b9cedea22d650cec583bfb298bc94d6469527360b338cdd6d7981f769ea0f26","observation_id":"4bf53128-0cce-45be-8410-0e84849907b6","resolution":{"observed_at":"2026-07-01T11:15:42.858675Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2011.03395/citation-record","integrity":"/paper/2011.03395/integrity","json":"/paper/2011.03395/citation-record.json","paper":"/paper/2011.03395"},"outbound":[],"paper":{"arxiv_id":"2011.03395","last_updated":"2020-11-24T19:16:02Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T12:11:27.017871Z","submitted_at":"2020-11-06T14:53:13Z","title":"Underspecification Presents Challenges for Credibility in Modern Machine Learning"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2011.03395."}