{"as_of":"2026-08-09T12:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:43009be4781c7be12b89539358a7be50248c6e37c88592b16b583967229a5ece","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:35:39.503749Z","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":"2026-07-01T09:55:40.140387Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2107.11277","last_updated":"2024-02-21T10:10:40Z","snapshot_observed_at":"2026-08-09T11:47:28.523729Z","submitted_at":"2021-07-23T14:43:56Z","title":"Machine Learning with a Reject Option: A survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.11277","snapshot_observed_at":"2026-08-07T10:35:39.503749Z","title":"Machine learning with a reject option: A survey","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.05252","last_updated":"2025-08-07T17:13:46Z","snapshot_observed_at":"2026-08-07T10:19:41.218011Z","submitted_at":"2025-06-05T17:13:59Z","title":"Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning","version":2},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-07T10:35:39.503749Z"},"links":{"cited_paper":"/paper/2107.11277","citing_paper":"/paper/2506.05252"},"observation_digest":"sha256:caedba20c8456bf450bbcf7245f90583f46b6300114107e3c261846b97185bc2","observation_id":"6dc1997f-8191-423c-b387-0249d5bb5556","resolution":{"observed_at":"2026-08-07T10:35:39.503749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.11277","last_updated":"2024-02-21T10:10:40Z","snapshot_observed_at":"2026-08-09T11:47:28.523729Z","submitted_at":"2021-07-23T14:43:56Z","title":"Machine Learning with a Reject Option: A survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.11277","snapshot_observed_at":"2026-08-07T00:42:19.800537Z","title":"Machine learning with a reject option: A survey, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13217","last_updated":"2025-06-16T08:16:54Z","snapshot_observed_at":"2026-08-07T00:33:27.488109Z","submitted_at":"2025-06-16T08:16:54Z","title":"Polyra Swarms: A Shape-Based Approach to Machine Learning","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:19.800537Z"},"links":{"cited_paper":"/paper/2107.11277","citing_paper":"/paper/2506.13217"},"observation_digest":"sha256:449dc1ff488fc9abf64c92cede53042980bff0020adf8c861e925473e93d65a4","observation_id":"5294b28f-0947-4e2f-9482-2e1539964ee8","resolution":{"observed_at":"2026-08-07T00:42:19.800537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.11277","last_updated":"2024-02-21T10:10:40Z","snapshot_observed_at":"2026-08-09T11:47:28.523729Z","submitted_at":"2021-07-23T14:43:56Z","title":"Machine Learning with a Reject Option: A survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.11277","snapshot_observed_at":"2026-08-04T08:46:36.807955Z","title":"arXiv preprint arXiv:2107.11277 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.19328","last_updated":"2026-05-23T15:34:18Z","snapshot_observed_at":"2026-08-04T08:46:32.037425Z","submitted_at":"2025-10-22T07:41:30Z","title":"Clustered Calibration: Representation-Aware Probability Calibration via Learned Subpopulations","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-04T08:46:36.807955Z"},"links":{"cited_paper":"/paper/2107.11277","citing_paper":"/paper/2510.19328"},"observation_digest":"sha256:3ab6c464492c2bb1b22395d7562731fca0b317362acfe93ce745fa12613d5015","observation_id":"7f35b16c-0fc0-4bbe-973a-b72ab5219827","resolution":{"observed_at":"2026-08-04T08:46:36.807955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.11277","last_updated":"2024-02-21T10:10:40Z","snapshot_observed_at":"2026-08-09T11:47:28.523729Z","submitted_at":"2021-07-23T14:43:56Z","title":"Machine Learning with a Reject Option: A survey","version":3},"cited_work":{"arxiv_id":"2107.11277","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2107.11277","snapshot_observed_at":"2026-07-01T09:55:40.140387Z","title":"Machine learning with a reject option: A survey","venue":null,"work_id":"880d7a80-9d33-4e4b-841a-34e989a947e7","year":2024},"citing_paper":{"arxiv_id":"2511.10370","last_updated":"2026-04-20T08:43:43Z","snapshot_observed_at":"2026-08-05T10:17:17.093620Z","submitted_at":"2025-11-13T14:48:55Z","title":"SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-17T22:20:32.857882Z"},"links":{"cited_paper":"/paper/2107.11277","citing_paper":"/paper/2511.10370"},"observation_digest":"sha256:742e60a7f0c117945a2f1949f11437d47ece42d829eb8067733e658fbbf476e8","observation_id":"dd9c4246-bdbe-4da3-94e7-87cee3e151c5","resolution":{"observed_at":"2026-05-17T22:22:09.021301Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.11277","last_updated":"2024-02-21T10:10:40Z","snapshot_observed_at":"2026-08-09T11:47:28.523729Z","submitted_at":"2021-07-23T14:43:56Z","title":"Machine Learning with a Reject Option: A survey","version":3},"cited_work":{"arxiv_id":"2107.11277","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2107.11277","snapshot_observed_at":"2026-07-01T09:55:40.140387Z","title":"Machine learning with a reject option: A survey","venue":null,"work_id":"880d7a80-9d33-4e4b-841a-34e989a947e7","year":2024},"citing_paper":{"arxiv_id":"2606.31331","last_updated":"2026-06-30T08:32:53Z","snapshot_observed_at":"2026-08-07T03:43:21.006277Z","submitted_at":"2026-06-30T08:32:53Z","title":"Expected Gain-based Escalation in Vertical Federated Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-01T06:09:52.967421Z"},"links":{"cited_paper":"/paper/2107.11277","citing_paper":"/paper/2606.31331"},"observation_digest":"sha256:a2f306d9da40d0472fa6159ec74b4766ec3030bf1cc388fe2aae45b3457f988a","observation_id":"b26c5238-6731-4667-b0bd-8bda50ad6bbd","resolution":{"observed_at":"2026-07-01T09:55:40.142462Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.11277","last_updated":"2024-02-21T10:10:40Z","snapshot_observed_at":"2026-08-09T11:47:28.523729Z","submitted_at":"2021-07-23T14:43:56Z","title":"Machine Learning with a Reject Option: A survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.11277","snapshot_observed_at":"2026-08-02T07:00:25.920267Z","title":"Machine learning with a reject option: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.11983","last_updated":"2026-07-15T02:23:38Z","snapshot_observed_at":"2026-08-02T07:00:22.920721Z","submitted_at":"2026-07-13T13:04:15Z","title":"Removable Defects: The Economics and Limits of Deliberate Deficiency","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-02T07:00:25.920267Z"},"links":{"cited_paper":"/paper/2107.11277","citing_paper":"/paper/2607.11983"},"observation_digest":"sha256:7042764e13e2c0d73483350e1af93e752341e0c98a20e3acfb80fc512f9acb76","observation_id":"e5342e89-ad64-44ff-9851-fab61e5765ef","resolution":{"observed_at":"2026-08-02T07:00:25.920267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2107.11277/citation-record","integrity":"/paper/2107.11277/integrity","json":"/paper/2107.11277/citation-record.json","paper":"/paper/2107.11277"},"outbound":[],"paper":{"arxiv_id":"2107.11277","last_updated":"2024-02-21T10:10:40Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T11:47:28.523729Z","submitted_at":"2021-07-23T14:43:56Z","title":"Machine Learning with a Reject Option: A survey"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2107.11277."}