{"as_of":"2026-08-08T16:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:52a2446aba1090de0d73cd016037f3bfafac6233f9fd6f1d93119a70647593a8","coverage":[{"denominator":8,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:35:35.182611Z","state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2507.21156/citation-record","integrity":"/paper/2507.21156/integrity","json":"/paper/2507.21156/citation-record.json","paper":"/paper/2507.21156"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:35:35.274608Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":"bb384e64-09da-4406-8bcc-e1d78ffde326","year":2021},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.158271Z"},"links":{"citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:95330f8178c58977c07591f303d390b9acc9a2f177330cf74a5f3dcb4f251a94","observation_id":"eb5b616d-38f7-4b0d-b031-66cc1269714b","resolution":{"observed_at":"2026-08-06T14:35:35.278073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T14:35:35.265276Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":"51f6d2c0-3bc3-4e0d-a08d-51b8a55c1333","year":2016},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.161922Z"},"links":{"citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:951e589c9be6841e6170f3b953569bd689751b252d3339c03af989fe542bc9ca","observation_id":"e76b4d87-826c-4ed2-b950-6e1cc50fe733","resolution":{"observed_at":"2026-08-06T14:35:35.268514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T14:35:35.255592Z","title":"EfficientNet: Rethinking model scaling for convolu- tional neural networks,","venue":null,"work_id":"66ea073a-c989-4c31-8660-5a22e726eed1","year":2019},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.165935Z"},"links":{"citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:108eaf8a48a2efe0cc2f5ac77fc19fccd27b544f82ddf506c1cc6a0a57f9c053","observation_id":"c72027e4-d733-41f1-9eb7-6e171558a396","resolution":{"observed_at":"2026-08-06T14:35:35.259047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T14:35:35.246203Z","title":"Training data-efficient image transformers & distillation through attention,","venue":null,"work_id":"1447065a-0ff7-4012-8873-caa71dae6688","year":2021},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.169197Z"},"links":{"citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:ce318335f53f51aae01602197da6d5c321f330120751d74d0515f98b1fa76b4f","observation_id":"45d9e4da-d8b4-41c6-9f02-bb2e878e4f60","resolution":{"observed_at":"2026-08-06T14:35:35.249524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05225","last_updated":"2017-12-25T11:09:06Z","snapshot_observed_at":"2026-08-06T22:13:27.249372Z","submitted_at":"2017-11-14T17:58:50Z","title":"CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05225","snapshot_observed_at":"2026-08-06T14:35:35.172513Z","title":"CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.172513Z"},"links":{"cited_paper":"/paper/1711.05225","citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:9e2ce03ef359eb453a92cdeb83726ce6c0e0ec623f58b6c11ec043b2c868dad0","observation_id":"3672a3f3-8ff3-4dd0-a83d-950a2c2ce2ad","resolution":{"observed_at":"2026-08-06T14:35:35.172513Z","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":"2026-08-06T14:35:35.236028Z","title":"Dermatologist-level classification of skin cancer with deep neural networks,","venue":null,"work_id":"6b9b7b61-5be4-4f2e-a6c4-296080f10115","year":2017},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.176350Z"},"links":{"citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:2265b8e0ff8a4172ac9cd794219a16bda38c06ca371f2cd408e8934a1c822975","observation_id":"3ac7279c-4cd9-47b6-8cd4-373d65594893","resolution":{"observed_at":"2026-08-06T14:35:35.239335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T14:35:35.222928Z","title":"Self-supervised learning for medical image analysis using image context restoration,","venue":null,"work_id":"10299f21-0062-472f-96b4-f037e87bc17c","year":2019},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.179618Z"},"links":{"citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:01f370628d846137e186f094432f4df0c1313fe1f180fca949667fa19aeeee20","observation_id":"966bfda8-a785-4dc9-b7f6-31ef331294b5","resolution":{"observed_at":"2026-08-06T14:35:35.229496Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.09038","last_updated":"2021-08-20T08:01:19Z","snapshot_observed_at":"2026-08-04T16:19:37.799838Z","submitted_at":"2021-08-20T08:01:19Z","title":"Is it Time to Replace CNNs with Transformers for Medical Images?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.09038","snapshot_observed_at":"2026-08-06T14:35:35.182611Z","title":"Is it time to replace CNNs with transformers for medical images?,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:35.182611Z"},"links":{"cited_paper":"/paper/2108.09038","citing_paper":"/paper/2507.21156"},"observation_digest":"sha256:09bd7676464858412fdce43f265e4c73a4b66621fa677e783f4f994d618a7a9d","observation_id":"ada758b0-85a0-4734-8aaf-acdc50cd7686","resolution":{"observed_at":"2026-08-06T14:35:35.182611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.21156","last_updated":"2025-07-24T19:40:13Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-08T11:30:35.256447Z","submitted_at":"2025-07-24T19:40:13Z","title":"Comparative Analysis of Vision Transformers and Convolutional Neural Networks for Medical Image Classification"},"reference_resolution":{"displayed":8,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":0,"verified_fuzzy":6},"total_outbound_references":8},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2507.21156."}