{"as_of":"2026-08-18T09:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8a44bacb314ab5d5298eb430e9f60d327d14cef7d758f5a96617584cab1d8f75","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":"2026-08-18T06:34:40.430872+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":"2026-08-14T15:22:10.388634Z","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":"2026-08-14T15:22:10.734997Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1801.06285","last_updated":"2018-01-19T03:30:35Z","snapshot_observed_at":"2026-08-15T17:02:41.767341Z","submitted_at":"2018-01-19T03:30:35Z","title":"Reinforcement Learning-based Energy Trading for Microgrids","version":1},"cited_work":{"arxiv_id":"1801.06285","doi":null,"metadata_source":"pith","pith_arxiv_id":"1801.06285","snapshot_observed_at":"2026-08-14T15:22:10.734997Z","title":"Reinforcement Learning-based Energy Trading for Microgrids","venue":"cs.SY","work_id":"34e3e579-770a-40e7-be77-43afd2632651","year":2018},"citing_paper":{"arxiv_id":"1908.01310","last_updated":"2019-08-04T10:06:14Z","snapshot_observed_at":"2026-08-14T15:14:40.718424Z","submitted_at":"2019-08-04T10:06:14Z","title":"A Dynamic Analysis of Energy Storage with Renewable and Diesel Generation using Volterra Equations","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T15:22:10.388634Z"},"links":{"cited_paper":"/paper/1801.06285","citing_paper":"/paper/1908.01310"},"observation_digest":"sha256:e840b39a2fb54ebbb7b2d85b9f9fbb8afc22fb4c12970aedfde6a6d6dbff1006","observation_id":"8a236d1d-b096-470b-be15-cbdc2079e3e4","resolution":{"observed_at":"2026-08-14T15:22:10.741103Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1801.06285/citation-record","integrity":"/paper/1801.06285/integrity","json":"/paper/1801.06285/citation-record.json","paper":"/paper/1801.06285"},"outbound":[],"paper":{"arxiv_id":"1801.06285","last_updated":"2018-01-19T03:30:35Z","latest_version":1,"primary_category":"cs.SY","snapshot_observed_at":"2026-08-15T17:02:41.767341Z","submitted_at":"2018-01-19T03:30:35Z","title":"Reinforcement Learning-based Energy Trading for Microgrids"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1801.06285."}