{"as_of":"2026-08-14T07:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d7b4001419ba20588a6d5ffc03b7bdd9bd2b74da5737eee1a9ef0b253077f6a5","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":"2026-08-14T06:32:32.682623+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":"2026-08-12T17:24:16.898241Z","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":"2026-08-12T18:16:22.223912Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2210.00987","last_updated":"2022-10-03T14:53:17Z","snapshot_observed_at":"2026-08-13T14:14:03.789749Z","submitted_at":"2022-10-03T14:53:17Z","title":"Data Budgeting for Machine Learning","version":1},"cited_work":{"arxiv_id":"2210.00987","doi":"10.48550/arxiv.2210.00987","metadata_source":"pith","pith_arxiv_id":"2210.00987","snapshot_observed_at":"2026-08-12T18:16:22.223912Z","title":"Data Budgeting for Machine Learning","venue":"cs.LG","work_id":"bf82b190-cb89-4bf9-bf61-0eba9071f6e0","year":2022},"citing_paper":{"arxiv_id":"2411.12636","last_updated":"2025-04-29T10:04:50Z","snapshot_observed_at":"2026-08-12T17:17:14.070292Z","submitted_at":"2024-11-19T16:49:58Z","title":"PyAWD: A Library for Generating Large Synthetic Datasets of Acoustic Wave Propagation","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T17:24:16.898241Z"},"links":{"cited_paper":"/paper/2210.00987","citing_paper":"/paper/2411.12636"},"observation_digest":"sha256:f8c2352a0531fd63d1dc0b5571cd7f3d467b578ad4bc6b660046545b16af7848","observation_id":"2deb2185-5570-4b91-8eb9-ae96f4b7e1bd","resolution":{"observed_at":"2026-08-12T17:24:16.937173Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2210.00987/citation-record","integrity":"/paper/2210.00987/integrity","json":"/paper/2210.00987/citation-record.json","paper":"/paper/2210.00987"},"outbound":[],"paper":{"arxiv_id":"2210.00987","last_updated":"2022-10-03T14:53:17Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T14:14:03.789749Z","submitted_at":"2022-10-03T14:53:17Z","title":"Data Budgeting for Machine Learning"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2210.00987."}