{"as_of":"2026-08-23T00:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ff1b3ebdd058531617f1600d97198b42516ac446ab686b57122d39b8dab61975","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:18:04.312243Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+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/2411.12707/citation-record","integrity":"/paper/2411.12707/integrity","json":"/paper/2411.12707/citation-record.json","paper":"/paper/2411.12707"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:18:04.227483Z","title":"Khandoker, Herbert F","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.227483Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:62c5e09c09f71f1b21a31a42ef3137b72d34d89cc4715a83ed1a95899959e2af","observation_id":"dd84bc7d-4c34-48f6-81fc-9f9cfbbf34e7","resolution":{"observed_at":"2026-08-12T17:18:04.227483Z","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":"2026-08-12T17:18:04.768700Z","title":"Revolutionizing healthcare: the role of artificial intelligence in clinical practice","venue":null,"work_id":"32395d5e-7da7-49e2-b6da-f510d6497a4b","year":2023},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.232341Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:910caba3fe7c17ce85d688b8cd771a0cbe1a60ab4a5d0bbbea3d49baa77fa21a","observation_id":"26d9846a-3ff5-474f-9bf3-b2dc4e5fb29b","resolution":{"observed_at":"2026-08-12T17:18:04.772728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.10356","last_updated":"2021-07-21T21:10:16Z","snapshot_observed_at":"2026-08-16T18:08:22.183610Z","submitted_at":"2021-07-21T21:10:16Z","title":"Reading Race: AI Recognises Patient's Racial Identity In Medical Images","version":1},"cited_work":{"arxiv_id":"2107.10356","doi":null,"metadata_source":"pith","pith_arxiv_id":"2107.10356","snapshot_observed_at":"2026-08-12T17:18:04.636007Z","title":"Reading Race: AI Recognises Patient's Racial Identity In Medical Images","venue":"cs.CV","work_id":"99ffa836-2e54-4336-b3bd-7ae9ce4c0223","year":2021},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.236408Z"},"links":{"cited_paper":"/paper/2107.10356","citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:dbf96e0ab5ab80354edbcbb4428c911715d7b30ae19bd64f43e4ac945e44a305","observation_id":"5c10ba6f-59ff-495d-abec-8570c756ea7d","resolution":{"observed_at":"2026-08-12T17:18:04.640159Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.757548Z","title":"The matthews correlation coefficient (mcc) should replace the roc auc as the standard metric for assessing binary classification","venue":null,"work_id":"caa19152-a75d-486e-8c95-1d4ef3549243","year":2023},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.240948Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:56f4341597a574197484e0dcaf0e9ebe0a30ee56e63a768fe0035c199446472c","observation_id":"debf69d9-1ce4-4b2e-bac9-b53f40b9d5dc","resolution":{"observed_at":"2026-08-12T17:18:04.761714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.245051Z","title":"Coburn, Keith T","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.245051Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:0adf5a2c5d3a27ca24033adffd9bddd52cdfb1b5f5cf4e0ff13f23ed54f8841e","observation_id":"e1bfceac-f376-4912-b33d-7aef570052b2","resolution":{"observed_at":"2026-08-12T17:18:04.245051Z","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/s00521-023-09074-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-18T11:03:46.223893Z","title":"Towards efficient image-based representation of tabular data","venue":"Neural Computing and Applications","work_id":"4b19fc9f-21f4-4217-b409-8c3dafcdf77d","year":2024},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.249518Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:5af15629ce935314633926e9383a27494c6035bb24d859815187105a7b3062c0","observation_id":"959c144a-21a9-4f11-9183-a412ab8e4fa9","resolution":{"observed_at":"2026-08-12T17:18:04.400757Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.745949Z","title":"Ai for radiographic covid-19 detection selects shortcuts over signal","venue":null,"work_id":"ebd44b90-db34-4d04-8136-7b22060e018b","year":2021},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.253387Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:957222fe3c68ecc5d57929d06394e85da8b2d66d9931638985ea3bfeafa234df","observation_id":"a737227f-2af5-4b2e-8973-a149657cdbe1","resolution":{"observed_at":"2026-08-12T17:18:04.750772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-031-12053-4_2","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-13T11:03:48.094449Z","title":"Papież, and Adam Mahdi","venue":"Lecture notes in computer science","work_id":"13dd3587-b2c4-4d5a-8e40-9357e4a676ac","year":2022},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.256877Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:3d3684297090b9cfb7f860dc3f3a3de2300f01ecb294eccd70c3a9922ee2d0b3","observation_id":"4d6b63d2-787f-4922-b0bd-a05510b827a7","resolution":{"observed_at":"2026-08-12T17:18:04.389699Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.260590Z","title":"Algorithmic encoding of protected characteristics in chest X -ray disease detection models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.260590Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:c68d0f43c9247cec4e6e3f85fff7d25361b3c3bf54af9e12ec7b0be9697d481c","observation_id":"435092da-28a6-4532-9734-c9496d12a708","resolution":{"observed_at":"2026-08-12T17:18:04.260590Z","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":"2026-08-12T17:18:04.264325Z","title":"Menten, and Daniel Rueckert","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.264325Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:0121c4fc4e693c6b1ecdda0e0ec1bb0647d62cc4e5197cc6130c99d45eb134de","observation_id":"ada67af6-402c-4bb3-8cdc-ff40613bbf96","resolution":{"observed_at":"2026-08-12T17:18:04.264325Z","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":"2026-08-12T17:18:04.267629Z","title":"Partridge, Habib Rahbar, Debosmita Biswas, Christoph I","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.267629Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:1aedbf8c557094d27c51a4cb3a428dbdd1f7d442b1b8c5aaf4acadb2e969eaf0","observation_id":"2b69419d-7425-420d-85eb-0d2c36be3264","resolution":{"observed_at":"2026-08-12T17:18:04.267629Z","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":"10.1002/mp.15903","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-13T11:03:48.094449Z","title":"Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma","venue":"Medical Physics","work_id":"52b00864-7dcf-498b-a6cf-dcdeb11d8052","year":2022},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.270938Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:56e1ac5b174afd3c7c362e3230b060c822e459dc0dbd08e2d256dd78265036a6","observation_id":"18e02c6e-8f36-4670-bb9e-075c987edadf","resolution":{"observed_at":"2026-08-12T17:18:04.379329Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.274445Z","title":"Mong, Safwan S","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.274445Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:5ac2f6ff9ad5f2ed562ca10d81132f6346ad222e268e144f117b75ae04e5a763","observation_id":"d2e319fd-2ff4-494e-bde3-d67b544e0e61","resolution":{"observed_at":"2026-08-12T17:18:04.274445Z","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":"2026-08-12T17:18:04.728774Z","title":"MIMIC - IV , a","venue":null,"work_id":"7f7f5c45-447c-48ab-a5f7-4cd0c875a721","year":null},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.277860Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:7703f39316c554a42458d8deda67e166d1727637e321285e60e2603e9e8303c9","observation_id":"628cc373-2c31-4374-99f1-fa6ffb2db740","resolution":{"observed_at":"2026-08-12T17:18:04.732810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.717710Z","title":"MIMIC - CXR - JPG - chest radiographs with structured labels, b","venue":null,"work_id":"08a9a7bd-2ded-4a86-885e-c1b5a36bbdc8","year":null},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.281673Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:a1da2f05994c92bcff36e6722a38feff07d31582910cecec166b38ff0bda5e1d","observation_id":"12b892e8-3dfb-476c-b851-5d5742d074a6","resolution":{"observed_at":"2026-08-12T17:18:04.721753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.285208Z","title":"Key challenges for delivering clinical impact with artificial intelligence","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.285208Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:d9c40269c2b73e0a5c873b437ba2fc9cebf1df7191a44de21275f98d0b654256","observation_id":"40725849-3ec1-4a89-85ba-f5dfa24ef7d0","resolution":{"observed_at":"2026-08-12T17:18:04.285208Z","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":"2026-08-12T17:18:04.288462Z","title":"Yan, Durgesh Chaudhary, Venkatesh Avula, Satish Mudiganti, Hannah Husby, Shima Shahjouei, Ardavan Afshar, Walter F","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.288462Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:34ed836e4749510cccb3a830aee841018959fe675292c223b67def660cbc6d99","observation_id":"6679f868-5798-4e4c-a0b3-d567cd20a0c5","resolution":{"observed_at":"2026-08-12T17:18:04.288462Z","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":"2026-08-12T17:18:04.292614Z","title":"A comparative analysis of converters of tabular data into image for the classification of Arboviruses using Convolutional Neural Networks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.292614Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:2bd2118efe3fdb4b17dd52b512d79d89c7e3648d5296c8e3192c44dea6ec564a","observation_id":"c22377ee-68a5-43c5-9ac9-86caebee5b64","resolution":{"observed_at":"2026-08-12T17:18:04.292614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6034","last_updated":"2014-04-19T11:54:52Z","snapshot_observed_at":"2026-08-17T14:45:30.096775Z","submitted_at":"2013-12-20T16:45:54Z","title":"Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6034","snapshot_observed_at":"2026-08-12T17:18:04.296867Z","title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.296867Z"},"links":{"cited_paper":"/paper/1312.6034","citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:38b1ade801d860b516f22beb1d7d8a961e0a17408571122c6d0d826c643ebf5e","observation_id":"9a2d0171-6978-4906-826c-a787047d30c6","resolution":{"observed_at":"2026-08-12T17:18:04.296867Z","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":"2026-08-12T17:18:04.300705Z","title":"Axiomatic attribution for deep networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.300705Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:8585d387162012e23bea5058895486f6f30fded672e79262acb4c6467afcc37b","observation_id":"534be826-0cec-41d0-83f5-1ff8b9d4b20e","resolution":{"observed_at":"2026-08-12T17:18:04.300705Z","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":"2026-08-12T17:18:04.305087Z","title":"Sanity Checks for Saliency Metrics","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.305087Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:cce4a0cac789b28efdfe9bb378a3d36554105800b6790b83e2792a1037ad7e57","observation_id":"e7d2b64b-d6a3-42ab-b14f-a983af021806","resolution":{"observed_at":"2026-08-12T17:18:04.305087Z","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":"10.1016/j.jclinepi.2022.12.011","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:18:04.344301Z","title":null,"venue":null,"work_id":"74236368-d765-4ce0-8531-4000da9841be","year":2023},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.308786Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:b96770a4a14952b67a3ffdd0c636dcec8a4892276037374f72c8d6b9ec9ceb09","observation_id":"6cbddf65-0117-4320-8f64-7cd2cc803116","resolution":{"observed_at":"2026-08-12T17:18:04.348738Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T17:18:04.312243Z","title":"Evrard, James H","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-12T17:18:04.312243Z"},"links":{"citing_paper":"/paper/2411.12707"},"observation_digest":"sha256:7506792f0748305158f18272acf8fce39a01db28c0a96c78b61933904d8fdf3e","observation_id":"a769e310-6922-430f-9fb1-804b8b0b0dcc","resolution":{"observed_at":"2026-08-12T17:18:04.312243Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.12707","last_updated":"2024-11-19T18:22:25Z","latest_version":1,"primary_category":"q-bio.QM","snapshot_observed_at":"2026-08-17T15:54:21.938504Z","submitted_at":"2024-11-19T18:22:25Z","title":"Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":13,"verified_exact":4,"verified_fuzzy":5},"total_outbound_references":23},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2411.12707."}