{"as_of":"2026-08-10T08:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:45f7602748623fd013437a0b28eb531b7f235d86761c3fb298b7b29d93b07da5","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:20:01.826147Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-18T20:22:50.669602Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.10134","snapshot_observed_at":"2026-08-06T23:20:01.826147Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.18679","last_updated":"2025-07-15T07:59:56Z","snapshot_observed_at":"2026-08-07T20:56:17.568068Z","submitted_at":"2025-06-23T14:22:49Z","title":"MARL-MambaContour: Unleashing Multi-Agent Deep Reinforcement Learning for Active Contour Optimization in Medical Image Segmentation","version":2},"reference_index":103,"source":"pdf_text","source_observed_at":"2026-08-06T23:20:01.826147Z"},"links":{"cited_paper":"/paper/2008.10134","citing_paper":"/paper/2506.18679"},"observation_digest":"sha256:273f2dffbf7c87fd3c26909a230ba6ed67091b2e5f30212563ca4a0fafc24402","observation_id":"db1807c7-8640-47f0-bac3-a24af135774f","resolution":{"observed_at":"2026-08-06T23:20:01.826147Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.10134","snapshot_observed_at":"2026-08-06T21:12:05.951336Z","title":"m2caiseg: Semantic segmentation of laparoscopic images using convolutional neural networks","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2507.00868","last_updated":"2025-07-02T09:16:31Z","snapshot_observed_at":"2026-08-10T03:51:48.691320Z","submitted_at":"2025-07-01T15:32:23Z","title":"Is Visual in-Context Learning for Compositional Medical Tasks within Reach?","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T21:12:05.951336Z"},"links":{"cited_paper":"/paper/2008.10134","citing_paper":"/paper/2507.00868"},"observation_digest":"sha256:b37828865850ab7da18b3bd9c704181c012498e7c753efb31d1102b376e37b48","observation_id":"cce3a26d-b517-4c25-99c0-ce275d97bc29","resolution":{"observed_at":"2026-08-06T21:12:05.951336Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":"2008.10134","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2008.10134","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"m2caiseg: Semantic seg- mentation of laparoscopic images using convolutional neural networks","venue":null,"work_id":"397ee842-b8bc-4a7b-803c-dcbf767c6d88","year":2008},"citing_paper":{"arxiv_id":"2508.20909","last_updated":"2026-05-08T06:39:51Z","snapshot_observed_at":"2026-08-04T15:16:30.376993Z","submitted_at":"2025-08-28T15:38:50Z","title":"Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-18T20:22:41.555806Z"},"links":{"cited_paper":"/paper/2008.10134","citing_paper":"/paper/2508.20909"},"observation_digest":"sha256:a77df2ad0aa9b04c811efa8a0bd2208b50541897fefec011decc77320ab4fdd1","observation_id":"5c157bdd-6b49-47d1-a839-c534eb2f6f17","resolution":{"observed_at":"2026-05-18T20:22:50.673017Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":"2008.10134","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2008.10134","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"m2caiseg: Semantic seg- mentation of laparoscopic images using convolutional neural networks","venue":null,"work_id":"397ee842-b8bc-4a7b-803c-dcbf767c6d88","year":2008},"citing_paper":{"arxiv_id":"2511.03769","last_updated":"2026-07-31T16:29:27Z","snapshot_observed_at":"2026-08-05T23:14:15.586617Z","submitted_at":"2025-11-05T16:44:01Z","title":"Current validation practice undermines surgical AI development","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-05-18T01:41:38.726003Z"},"links":{"cited_paper":"/paper/2008.10134","citing_paper":"/paper/2511.03769"},"observation_digest":"sha256:ec816a74e2c0237635a0b5d1e7573af7d327b5a9e59997e0dc8eb1de1c8e28dd","observation_id":"6ba67db0-b999-40d9-98ec-e94afeb35dae","resolution":{"observed_at":"2026-05-18T01:42:17.474629Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.10134","snapshot_observed_at":"2026-08-03T23:55:25.398363Z","title":"m2caiseg: Semantic segmentation of laparoscopic images using convolutional neural networks.arXiv preprint arXiv:2008.10134, 2020","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2511.03769","last_updated":"2026-07-31T16:29:27Z","snapshot_observed_at":"2026-08-05T23:14:15.586617Z","submitted_at":"2025-11-05T16:44:01Z","title":"Current validation practice undermines surgical AI development","version":3},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-03T23:55:25.398363Z"},"links":{"cited_paper":"/paper/2008.10134","citing_paper":"/paper/2511.03769"},"observation_digest":"sha256:0ee123e0f1a182bd5eec15b2736427ea893231af402457cd9636ca6fc1925132","observation_id":"801bd23c-d565-48be-b969-987b778efccb","resolution":{"observed_at":"2026-08-03T23:55:25.398363Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":"2008.10134","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2008.10134","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"m2caiseg: Semantic seg- mentation of laparoscopic images using convolutional neural networks","venue":null,"work_id":"397ee842-b8bc-4a7b-803c-dcbf767c6d88","year":2008},"citing_paper":{"arxiv_id":"2604.02877","last_updated":"2026-04-03T08:42:51Z","snapshot_observed_at":"2026-08-05T22:43:50.067352Z","submitted_at":"2026-04-03T08:42:51Z","title":"Unlocking Positive Transfer in Incrementally Learning Surgical Instruments: A Self-reflection Hierarchical Prompt Framework","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-13T20:58:29.515826Z"},"links":{"cited_paper":"/paper/2008.10134","citing_paper":"/paper/2604.02877"},"observation_digest":"sha256:58326688cd1617537f4326e92cc268576dcb22b199626ab5ba475a2bd27ae823","observation_id":"a4369137-fb50-48ee-aab2-babb32137843","resolution":{"observed_at":"2026-05-13T21:03:20.370387Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":"2008.10134","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2008.10134","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"m2caiseg: Semantic seg- mentation of laparoscopic images using convolutional neural networks","venue":null,"work_id":"397ee842-b8bc-4a7b-803c-dcbf767c6d88","year":2008},"citing_paper":{"arxiv_id":"2604.05651","last_updated":"2026-04-07T09:54:37Z","snapshot_observed_at":"2026-07-06T22:54:21.571606Z","submitted_at":"2026-04-07T09:54:37Z","title":"Probing Intrinsic Medical Task Relationships: A Contrastive Learning Perspective","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-10T19:54:48.926387Z"},"links":{"cited_paper":"/paper/2008.10134","citing_paper":"/paper/2604.05651"},"observation_digest":"sha256:7bd228575ae469e64fd193a51cea9db556f8f2e1cd6cffea7f8e8b804d08173f","observation_id":"9d13ed2a-9006-4ca9-8ad8-2c4aeb8b28bd","resolution":{"observed_at":"2026-05-10T22:25:50.174780Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2008.10134/citation-record","integrity":"/paper/2008.10134/integrity","json":"/paper/2008.10134/citation-record.json","paper":"/paper/2008.10134"},"outbound":[],"paper":{"arxiv_id":"2008.10134","last_updated":"2020-12-10T21:34:59Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T00:36:19.430260Z","submitted_at":"2020-08-23T23:30:15Z","title":"m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2008.10134."}