{"as_of":"2026-08-23T08:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d08dda4e7195cde16e6136161290e8f77ee07b3f2bb0ad8616ae6b30785e0fab","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":"2026-08-23T06:30:58.430688+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":"2026-08-15T18:12:54.118546Z","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":"2026-08-15T18:12:54.150923Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.11457","last_updated":"2024-05-19T05:58:44Z","snapshot_observed_at":"2026-08-16T13:51:35.401944Z","submitted_at":"2024-05-19T05:58:44Z","title":"Deep Dive into Model-free Reinforcement Learning for Biological and Robotic Systems: Theory and Practice","version":1},"cited_work":{"arxiv_id":"2405.11457","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.11457","snapshot_observed_at":"2026-08-15T18:12:54.150923Z","title":"Deep Dive into Model-free Reinforcement Learning for Biological and Robotic Systems: Theory and Practice","venue":"cs.RO","work_id":"8fb8187d-4569-4c5e-92ed-9466f711d918","year":2024},"citing_paper":{"arxiv_id":"2507.18849","last_updated":"2025-07-24T23:38:06Z","snapshot_observed_at":"2026-08-17T08:45:21.308016Z","submitted_at":"2025-07-24T23:38:06Z","title":"Optimizing Metachronal Paddling with Reinforcement Learning at Low Reynolds Number","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T18:12:54.118546Z"},"links":{"cited_paper":"/paper/2405.11457","citing_paper":"/paper/2507.18849"},"observation_digest":"sha256:e2bf8de0b5f85a53512caea21e7d839e516bc8754ac6e7fe5e2814727cb3141f","observation_id":"634e1531-2a30-4287-bf49-b7696c379ce7","resolution":{"observed_at":"2026-08-15T18:12:54.157032Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.11457/citation-record","integrity":"/paper/2405.11457/integrity","json":"/paper/2405.11457/citation-record.json","paper":"/paper/2405.11457"},"outbound":[],"paper":{"arxiv_id":"2405.11457","last_updated":"2024-05-19T05:58:44Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-16T13:51:35.401944Z","submitted_at":"2024-05-19T05:58:44Z","title":"Deep Dive into Model-free Reinforcement Learning for Biological and Robotic Systems: Theory and Practice"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2405.11457."}