{"as_of":"2026-07-22T04:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8f7ba40a555cef436c18208dc756afa8ae9d514f719f640e1678b563a59b1c51","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":"2026-07-21T06:31:05.380196+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":"2026-05-07T15:20:23.340151Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T00:26:17.926254Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2106.09798","last_updated":"2023-02-13T15:34:39Z","snapshot_observed_at":"2026-07-06T11:20:32.533833Z","submitted_at":"2021-06-17T20:25:38Z","title":"Wide stochastic networks: Gaussian limit and PAC-Bayesian training","version":3},"cited_work":{"arxiv_id":"2106.09798","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.09798","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Arxiv: 2106.09798 , year =","venue":null,"work_id":"b768e7aa-d631-4e4b-ad69-7efb272da721","year":null},"citing_paper":{"arxiv_id":"2605.03772","last_updated":"2026-05-05T14:03:25Z","snapshot_observed_at":"2026-07-06T23:16:40.201701Z","submitted_at":"2026-05-05T14:03:25Z","title":"On the Induced Norms of Matrices and Grothendieck problems","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-05-07T15:20:23.340151Z"},"links":{"cited_paper":"/paper/2106.09798","citing_paper":"/paper/2605.03772"},"observation_digest":"sha256:eed17cde511628c85219de92fcc3d73b1367c4c5e7ccb7a4ecdba2b4bacddc7c","observation_id":"483a3d90-94da-4cbf-9bd1-b8d2a33b5812","resolution":{"observed_at":"2026-05-12T00:26:17.929164Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-21T06:31:05.380196+00:00","source":"crossref"},{"observed_at":"2026-07-21T06:31:00.184556+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2106.09798/citation-record","integrity":"/paper/2106.09798/integrity","json":"/paper/2106.09798/citation-record.json","paper":"/paper/2106.09798"},"outbound":[],"paper":{"arxiv_id":"2106.09798","last_updated":"2023-02-13T15:34:39Z","latest_version":3,"primary_category":"stat.ML","snapshot_observed_at":"2026-07-06T11:20:32.533833Z","submitted_at":"2021-06-17T20:25:38Z","title":"Wide stochastic networks: Gaussian limit and PAC-Bayesian training"},"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":"2026-07-21T06:31:05.380196+00:00","source":"crossref"},{"observed_at":"2026-07-21T06:31:00.184556+00:00","source":"retraction_watch"}],"thesis":"As of 22 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2106.09798."}