{"as_of":"2026-08-10T22:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:66fc27c7629eadf509c8a56b9b3c5a011d78528630105dcade9e66982a65bdc0","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-10T18:50:14.375126Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-10T18:57:31.648107Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.17772","last_updated":"2025-08-25T21:43:21Z","snapshot_observed_at":"2026-07-06T16:39:12.627366Z","submitted_at":"2023-10-26T20:37:29Z","title":"Learning Optimal Classification Trees Robust to Distribution Shifts","version":3},"cited_work":{"arxiv_id":"2310.17772","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.17772","snapshot_observed_at":"2026-07-10T18:57:31.648107Z","title":"Learning Optimal Classification Trees Robust to Distribution Shifts","venue":"cs.LG","work_id":"bda82d39-e17f-4e05-9484-2c7bbf20b38c","year":2023},"citing_paper":{"arxiv_id":"2607.07762","last_updated":"2026-07-08T15:27:30Z","snapshot_observed_at":"2026-08-04T13:31:34.079041Z","submitted_at":"2026-07-08T15:27:30Z","title":"Trustworthy Machine Learning through the Lens of Combinatorial Optimization: Survey and Research Perspectives","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-10T18:50:14.375126Z"},"links":{"cited_paper":"/paper/2310.17772","citing_paper":"/paper/2607.07762"},"observation_digest":"sha256:706c42cb76dc39c5f9a78f77276506658d04e758ae9755e59022dc94f1515a93","observation_id":"f591889f-5bf3-4d51-9291-ab9afe78b14f","resolution":{"observed_at":"2026-07-10T18:57:31.649545Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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/2310.17772/citation-record","integrity":"/paper/2310.17772/integrity","json":"/paper/2310.17772/citation-record.json","paper":"/paper/2310.17772"},"outbound":[],"paper":{"arxiv_id":"2310.17772","last_updated":"2025-08-25T21:43:21Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T16:39:12.627366Z","submitted_at":"2023-10-26T20:37:29Z","title":"Learning Optimal Classification Trees Robust to Distribution Shifts"},"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 1 inbound Pith citation observation for arXiv:2310.17772."}