{"as_of":"2026-08-08T12:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b342ef4a29843983564ac1efed9f7031cbb44f48ed4d11971d600b947dabef9a","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":"2026-08-08T06:32:00.761636+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":"2026-08-06T13:21:59.021811Z","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":"2026-08-06T13:22:00.080600Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2008.02545","last_updated":"2021-04-26T09:05:48Z","snapshot_observed_at":"2026-07-06T09:45:01.182512Z","submitted_at":"2020-08-06T09:50:29Z","title":"A deep network construction that adapts to intrinsic dimensionality beyond the domain","version":3},"cited_work":{"arxiv_id":"2008.02545","doi":null,"metadata_source":"pith","pith_arxiv_id":"2008.02545","snapshot_observed_at":"2026-08-06T13:22:00.080600Z","title":"A deep network construction that adapts to intrinsic dimensionality beyond the domain","venue":"stat.ML","work_id":"9d56b87e-4300-4cd5-a5ba-64f888473102","year":2020},"citing_paper":{"arxiv_id":"2507.20853","last_updated":"2025-07-28T14:06:44Z","snapshot_observed_at":"2026-08-06T16:02:23.108264Z","submitted_at":"2025-07-28T14:06:44Z","title":"Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T13:21:59.021811Z"},"links":{"cited_paper":"/paper/2008.02545","citing_paper":"/paper/2507.20853"},"observation_digest":"sha256:d7bc00f319e75f277b73496a2e204231d65e5baa0ce313dd8c53a8777147ac25","observation_id":"18e78182-2133-43cd-b0f4-c06d67d9d51b","resolution":{"observed_at":"2026-08-06T13:22:00.099013Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2008.02545/citation-record","integrity":"/paper/2008.02545/integrity","json":"/paper/2008.02545/citation-record.json","paper":"/paper/2008.02545"},"outbound":[],"paper":{"arxiv_id":"2008.02545","last_updated":"2021-04-26T09:05:48Z","latest_version":3,"primary_category":"stat.ML","snapshot_observed_at":"2026-07-06T09:45:01.182512Z","submitted_at":"2020-08-06T09:50:29Z","title":"A deep network construction that adapts to intrinsic dimensionality beyond the domain"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2008.02545."}