{"as_of":"2026-08-13T19:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d1ce2d8a84f4771789ce925bd29afcf20a32b0fa4727f8705e6ee1116975e483","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":"2026-08-13T06:32:02.005865+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":"2026-08-07T00:33:59.916151Z","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":"2026-05-11T21:11:18.710290Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2104.03760","last_updated":"2021-04-08T13:26:30Z","snapshot_observed_at":"2026-08-13T07:15:20.412829Z","submitted_at":"2021-04-08T13:26:30Z","title":"A Reinforcement Learning Environment For Job-Shop Scheduling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.03760","snapshot_observed_at":"2026-08-07T00:33:59.916151Z","title":"A Reinforcement Learning Environment For Job-Shop Scheduling,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.13566","last_updated":"2025-06-17T15:27:49Z","snapshot_observed_at":"2026-08-07T00:27:51.180149Z","submitted_at":"2025-06-16T14:50:26Z","title":"A Production Scheduling Framework for Reinforcement Learning Under Real-World Constraints","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T00:33:59.916151Z"},"links":{"cited_paper":"/paper/2104.03760","citing_paper":"/paper/2506.13566"},"observation_digest":"sha256:15d57e896691cddfbf3f35509f00993c9753db8d402de2660fccc962845d2b5e","observation_id":"07132646-8924-4ce1-95a9-3fc4ef096c01","resolution":{"observed_at":"2026-08-07T00:33:59.916151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.03760","last_updated":"2021-04-08T13:26:30Z","snapshot_observed_at":"2026-08-13T07:15:20.412829Z","submitted_at":"2021-04-08T13:26:30Z","title":"A Reinforcement Learning Environment For Job-Shop Scheduling","version":1},"cited_work":{"arxiv_id":"2104.03760","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.03760","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A reinforcement learning environment for job-shop scheduling","venue":null,"work_id":"94fb8ba9-566d-4b32-adf7-29a10b1b72f5","year":2021},"citing_paper":{"arxiv_id":"2604.23841","last_updated":"2026-04-26T19:00:34Z","snapshot_observed_at":"2026-08-13T16:33:10.090778Z","submitted_at":"2026-04-26T19:00:34Z","title":"Scalable Production Scheduling: Linear Complexity via Unified Homogeneous Graphs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T06:31:39.576361Z"},"links":{"cited_paper":"/paper/2104.03760","citing_paper":"/paper/2604.23841"},"observation_digest":"sha256:b5347834f2ad87014cfabb7f3e674b527369f6d9e05302a689162bf68ec54dbc","observation_id":"08ede8cc-e1fb-4150-bb71-e0f273b40dc0","resolution":{"observed_at":"2026-05-11T21:11:18.713113Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2104.03760/citation-record","integrity":"/paper/2104.03760/integrity","json":"/paper/2104.03760/citation-record.json","paper":"/paper/2104.03760"},"outbound":[],"paper":{"arxiv_id":"2104.03760","last_updated":"2021-04-08T13:26:30Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T07:15:20.412829Z","submitted_at":"2021-04-08T13:26:30Z","title":"A Reinforcement Learning Environment For Job-Shop Scheduling"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.03760."}