{"as_of":"2026-08-09T07:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8b4d5416da591c6cb5bc60e7dc71b19af9ab643bb649ccc7771dc38fe9cbdded","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T20:51:32.513704Z","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":"2026-08-07T12:40:44.317405Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.00570","last_updated":"2020-05-01T18:56:18Z","snapshot_observed_at":"2026-07-06T09:16:56.708811Z","submitted_at":"2020-05-01T18:56:18Z","title":"When Ensembling Smaller Models is More Efficient than Single Large Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.00570","snapshot_observed_at":"2026-08-08T20:51:32.513704Z","title":"Leo Breiman","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2502.15740","last_updated":"2025-02-07T14:32:20Z","snapshot_observed_at":"2026-08-09T06:20:56.997307Z","submitted_at":"2025-02-07T14:32:20Z","title":"Detection of LLM-Generated Java Code Using Discretized Nested Bigrams","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T20:51:32.513704Z"},"links":{"cited_paper":"/paper/2005.00570","citing_paper":"/paper/2502.15740"},"observation_digest":"sha256:eeb7ea77261c55463aaf54c3fbbd7fd3130d4bc0fbb2044817a2f4a165a3ec6d","observation_id":"647b6fec-f673-4b6a-9058-ba3d67dbf55d","resolution":{"observed_at":"2026-08-08T20:51:32.513704Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.00570","last_updated":"2020-05-01T18:56:18Z","snapshot_observed_at":"2026-07-06T09:16:56.708811Z","submitted_at":"2020-05-01T18:56:18Z","title":"When Ensembling Smaller Models is More Efficient than Single Large Models","version":1},"cited_work":{"arxiv_id":"2005.00570","doi":null,"metadata_source":"pith","pith_arxiv_id":"2005.00570","snapshot_observed_at":"2026-08-07T12:40:44.317405Z","title":"When Ensembling Smaller Models is More Efficient than Single Large Models","venue":"cs.LG","work_id":"6cefe182-11a9-4af4-b90b-dd74e6a9d22c","year":2020},"citing_paper":{"arxiv_id":"2505.23947","last_updated":"2025-05-29T18:56:45Z","snapshot_observed_at":"2026-08-09T03:14:57.034243Z","submitted_at":"2025-05-29T18:56:45Z","title":"Position: The Future of Bayesian Prediction Is Prior-Fitted","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-07T12:40:38.615941Z"},"links":{"cited_paper":"/paper/2005.00570","citing_paper":"/paper/2505.23947"},"observation_digest":"sha256:0dae9cfb22f6dd69a812d39d2d1eaa86d9d8ec333c414b986db1ed653a3be248","observation_id":"bb0110ac-9ae2-4d8d-94c4-b688633be52a","resolution":{"observed_at":"2026-08-07T12:40:44.408942Z","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/2005.00570/citation-record","integrity":"/paper/2005.00570/integrity","json":"/paper/2005.00570/citation-record.json","paper":"/paper/2005.00570"},"outbound":[],"paper":{"arxiv_id":"2005.00570","last_updated":"2020-05-01T18:56:18Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T09:16:56.708811Z","submitted_at":"2020-05-01T18:56:18Z","title":"When Ensembling Smaller Models is More Efficient than Single Large 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 2 inbound Pith citation observations for arXiv:2005.00570."}