{"as_of":"2026-08-09T13:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ced5ffea8ff96e82fa70c4f8df9db8d4cd9d20104e59c98a0ef88110677fdae8","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":"2026-08-09T06:31:02.800959+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":"2026-08-07T20:24:08.220721Z","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":"2026-08-07T20:24:08.313829Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2210.12122","last_updated":"2022-10-21T17:22:03Z","snapshot_observed_at":"2026-07-06T14:08:49.704572Z","submitted_at":"2022-10-21T17:22:03Z","title":"Targeted active learning for probabilistic models","version":1},"cited_work":{"arxiv_id":"2210.12122","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.12122","snapshot_observed_at":"2026-08-07T20:24:08.313829Z","title":"Targeted active learning for probabilistic models","venue":"cs.LG","work_id":"f2f532ef-7d74-4c08-ab6b-50a2c752a730","year":2022},"citing_paper":{"arxiv_id":"2502.09829","last_updated":"2025-02-14T00:07:02Z","snapshot_observed_at":"2026-08-07T20:18:15.459594Z","submitted_at":"2025-02-14T00:07:02Z","title":"Efficient Evaluation of Multi-Task Robot Policies With Active Experiment Selection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T20:24:08.220721Z"},"links":{"cited_paper":"/paper/2210.12122","citing_paper":"/paper/2502.09829"},"observation_digest":"sha256:7bc916109ab906762d13d3aaa1e475220873b652cfb67ec3c19cada61f425219","observation_id":"53efac60-5367-47f7-b1ca-6fe513fef398","resolution":{"observed_at":"2026-08-07T20:24:08.321102Z","resolver_source":"local_arxiv","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"}}],"links":{"evidence":"/evidence","html":"/paper/2210.12122/citation-record","integrity":"/paper/2210.12122/integrity","json":"/paper/2210.12122/citation-record.json","paper":"/paper/2210.12122"},"outbound":[],"paper":{"arxiv_id":"2210.12122","last_updated":"2022-10-21T17:22:03Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T14:08:49.704572Z","submitted_at":"2022-10-21T17:22:03Z","title":"Targeted active learning for probabilistic models"},"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 1 inbound Pith citation observation for arXiv:2210.12122."}