{"as_of":"2026-08-06T12:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:de72d4eca4d6c9a99dba6fb1bdb89a0d84e0438390c09073a5869da6a1583759","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":"2026-08-06T06:34:29.942622+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":"2026-07-03T14:11:08.611671Z","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":"2026-07-03T14:18:22.543170Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2112.10664","last_updated":"2021-12-20T16:40:26Z","snapshot_observed_at":"2026-08-04T15:38:17.608179Z","submitted_at":"2021-12-20T16:40:26Z","title":"Proving Theorems using Incremental Learning and Hindsight Experience Replay","version":1},"cited_work":{"arxiv_id":"2112.10664","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2112.10664","snapshot_observed_at":"2026-07-03T14:18:22.543170Z","title":null,"venue":null,"work_id":"a88e4a92-68b8-45fc-ab43-6f2194bdcbab","year":null},"citing_paper":{"arxiv_id":"2607.01734","last_updated":"2026-07-02T05:44:10Z","snapshot_observed_at":"2026-07-07T00:07:13.555571Z","submitted_at":"2026-07-02T05:44:10Z","title":"Reformalization of the Jordan Curve Theorem","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-03T14:11:08.611671Z"},"links":{"cited_paper":"/paper/2112.10664","citing_paper":"/paper/2607.01734"},"observation_digest":"sha256:8d4b7728d6ae28f7882b9b8c9736a29126c02da198b195ac1499d8f82ad6760e","observation_id":"e090665e-d939-4056-afe4-2d32e5b9fc39","resolution":{"observed_at":"2026-07-03T14:18:22.544461Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2112.10664/citation-record","integrity":"/paper/2112.10664/integrity","json":"/paper/2112.10664/citation-record.json","paper":"/paper/2112.10664"},"outbound":[],"paper":{"arxiv_id":"2112.10664","last_updated":"2021-12-20T16:40:26Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-04T15:38:17.608179Z","submitted_at":"2021-12-20T16:40:26Z","title":"Proving Theorems using Incremental Learning and Hindsight Experience Replay"},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2112.10664."}