{"as_of":"2026-08-10T11:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4a98e8005983fd3d998611a1b1e52f741ca10877fe9d751114ce6de6f01adac8","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":"2026-08-10T06:31:04.303077+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":"2026-08-06T14:43:09.842065Z","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":"2026-08-06T18:16:30.548575Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1811.03172","last_updated":"2018-11-07T22:41:52Z","snapshot_observed_at":"2026-08-10T06:11:43.007178Z","submitted_at":"2018-11-07T22:41:52Z","title":"Opportunities in Machine Learning for Particle Accelerators","version":1},"cited_work":{"arxiv_id":"1811.03172","doi":"10.48550/arxiv.1811.03172","metadata_source":"pith","pith_arxiv_id":"1811.03172","snapshot_observed_at":"2026-08-06T18:16:30.548575Z","title":"Opportunities in Machine Learning for Particle Accelerators","venue":"physics.acc-ph","work_id":"29ec1953-7f5b-40d1-8bca-01ac5943e5b1","year":2018},"citing_paper":{"arxiv_id":"2507.17881","last_updated":"2025-07-23T19:14:46Z","snapshot_observed_at":"2026-08-10T11:09:10.204247Z","submitted_at":"2025-07-23T19:14:46Z","title":"A Supervised Machine Learning Framework for Multipactor Breakdown Prediction in High-Power Radio Frequency Devices and Accelerator Components: A Case Study in Planar Geometry","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-06T14:43:09.842065Z"},"links":{"cited_paper":"/paper/1811.03172","citing_paper":"/paper/2507.17881"},"observation_digest":"sha256:d75c49fa6ce62646e147fdecbe47034af689bf7eaf69c226d16535f2638ef46b","observation_id":"95903c7c-da21-46ea-872d-e14043fc55aa","resolution":{"observed_at":"2026-08-06T14:43:11.544386Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.03172","last_updated":"2018-11-07T22:41:52Z","snapshot_observed_at":"2026-08-10T06:11:43.007178Z","submitted_at":"2018-11-07T22:41:52Z","title":"Opportunities in Machine Learning for Particle Accelerators","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.03172","snapshot_observed_at":"2026-08-02T01:37:28.754780Z","title":"arXiv preprint arXiv:1811.03172 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.14619","last_updated":"2026-07-16T06:32:19Z","snapshot_observed_at":"2026-08-02T19:49:06.949474Z","submitted_at":"2026-07-16T06:32:19Z","title":"Machine Learning for Complex Instrument Design and Optimization","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-02T01:37:28.754780Z"},"links":{"cited_paper":"/paper/1811.03172","citing_paper":"/paper/2607.14619"},"observation_digest":"sha256:a67b6e431ac05223bf89f8a1b80fe23b66e9653d3d18aa0421401010946d4e31","observation_id":"f9e193f5-d798-42cd-af06-36279d8f124b","resolution":{"observed_at":"2026-08-02T01:37:28.754780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1811.03172/citation-record","integrity":"/paper/1811.03172/integrity","json":"/paper/1811.03172/citation-record.json","paper":"/paper/1811.03172"},"outbound":[],"paper":{"arxiv_id":"1811.03172","last_updated":"2018-11-07T22:41:52Z","latest_version":1,"primary_category":"physics.acc-ph","snapshot_observed_at":"2026-08-10T06:11:43.007178Z","submitted_at":"2018-11-07T22:41:52Z","title":"Opportunities in Machine Learning for Particle Accelerators"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1811.03172."}