{"as_of":"2026-08-14T14:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fea31e5a86cc9f7d3e2c5774475200def6f87ccf2a9e0fb73cfd3655cb173e1d","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":"2026-08-08T20:10:00.171189Z","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":"2026-08-08T20:10:01.897385Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1803.08604","last_updated":"2018-03-22T22:39:32Z","snapshot_observed_at":"2026-07-06T06:29:48.164531Z","submitted_at":"2018-03-22T22:39:32Z","title":"Learning State Representations for Query Optimization with Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"1803.08604","doi":null,"metadata_source":"pith","pith_arxiv_id":"1803.08604","snapshot_observed_at":"2026-08-08T20:10:01.897385Z","title":"Learning State Representations for Query Optimization with Deep Reinforcement Learning","venue":"cs.DB","work_id":"a402b337-b60c-4cce-9bae-f0ab904f4eeb","year":2018},"citing_paper":{"arxiv_id":"2502.05256","last_updated":"2025-02-07T18:20:19Z","snapshot_observed_at":"2026-08-12T05:34:53.050696Z","submitted_at":"2025-02-07T18:20:19Z","title":"Learned Offline Query Planning via Bayesian Optimization","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-08T20:10:00.171189Z"},"links":{"cited_paper":"/paper/1803.08604","citing_paper":"/paper/2502.05256"},"observation_digest":"sha256:c610cfc6c15117d0f08fc9d4f2e5c8dbfaaa7831433db5ffce3e09ec91b30878","observation_id":"51f5b556-03bc-43ff-8bc1-34ea96e042f4","resolution":{"observed_at":"2026-08-08T20:10:01.902376Z","resolver_source":"local_arxiv","status":"verified_exact"},"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/1803.08604/citation-record","integrity":"/paper/1803.08604/integrity","json":"/paper/1803.08604/citation-record.json","paper":"/paper/1803.08604"},"outbound":[],"paper":{"arxiv_id":"1803.08604","last_updated":"2018-03-22T22:39:32Z","latest_version":1,"primary_category":"cs.DB","snapshot_observed_at":"2026-07-06T06:29:48.164531Z","submitted_at":"2018-03-22T22:39:32Z","title":"Learning State Representations for Query Optimization with Deep Reinforcement 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:1803.08604."}