{"as_of":"2026-08-14T13:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:368ccd5a0e4734cab577f1dc8935713d6b4d3b26726a34bf84b130ec86d4edd9","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T23:37:30.017773Z","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":"2026-08-05T05:29:33.240403Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2210.01680","last_updated":"2023-02-03T18:44:47Z","snapshot_observed_at":"2026-08-13T14:13:18.294861Z","submitted_at":"2022-10-04T15:22:56Z","title":"New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.01680","snapshot_observed_at":"2026-08-09T23:37:30.017773Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18419","last_updated":"2025-03-02T02:18:54Z","snapshot_observed_at":"2026-08-13T21:29:08.647496Z","submitted_at":"2025-01-30T15:16:09Z","title":"Optimizers for Stabilizing Likelihood-free Inference","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T23:37:30.017773Z"},"links":{"cited_paper":"/paper/2210.01680","citing_paper":"/paper/2501.18419"},"observation_digest":"sha256:e5463bc002eec24d02d549c63b4be3b02ca0649e757a9259d101d3f2ada595cf","observation_id":"aab17975-0016-4a6b-b154-0ea6d17a8f25","resolution":{"observed_at":"2026-08-09T23:37:30.017773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.01680","last_updated":"2023-02-03T18:44:47Z","snapshot_observed_at":"2026-08-13T14:13:18.294861Z","submitted_at":"2022-10-04T15:22:56Z","title":"New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.01680","snapshot_observed_at":"2026-08-05T13:28:03.673381Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.00672","last_updated":"2025-08-31T02:54:40Z","snapshot_observed_at":"2026-08-14T01:05:08.092311Z","submitted_at":"2025-08-31T02:54:40Z","title":"Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T13:28:03.673381Z"},"links":{"cited_paper":"/paper/2210.01680","citing_paper":"/paper/2509.00672"},"observation_digest":"sha256:185d5fc693836fa74c9c7cd604b8439d264ce5f4cd4bde99622e438804b49870","observation_id":"03902bbf-89b7-4c8b-9a8d-edd731bd1525","resolution":{"observed_at":"2026-08-05T13:28:03.673381Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.01680","last_updated":"2023-02-03T18:44:47Z","snapshot_observed_at":"2026-08-13T14:13:18.294861Z","submitted_at":"2022-10-04T15:22:56Z","title":"New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation","version":2},"cited_work":{"arxiv_id":"2210.01680","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.01680","snapshot_observed_at":"2026-08-05T05:29:33.240403Z","title":"New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation","venue":"stat.ML","work_id":"ebb98b2d-d089-4401-9ec6-265e50ee3353","year":2022},"citing_paper":{"arxiv_id":"2509.05409","last_updated":"2026-08-07T14:29:34Z","snapshot_observed_at":"2026-08-14T03:27:37.722221Z","submitted_at":"2025-09-05T18:00:02Z","title":"Unbinning global LHC analyses","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-05T05:29:30.507669Z"},"links":{"cited_paper":"/paper/2210.01680","citing_paper":"/paper/2509.05409"},"observation_digest":"sha256:9b9168451c2ce5d0988cb60f3ae30f4f8ab5d1b2c3a6abede117792a9a86a033","observation_id":"672367d8-835b-4aa1-b876-a776a5367174","resolution":{"observed_at":"2026-08-05T05:29:33.245867Z","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/2210.01680/citation-record","integrity":"/paper/2210.01680/integrity","json":"/paper/2210.01680/citation-record.json","paper":"/paper/2210.01680"},"outbound":[],"paper":{"arxiv_id":"2210.01680","last_updated":"2023-02-03T18:44:47Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-13T14:13:18.294861Z","submitted_at":"2022-10-04T15:22:56Z","title":"New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation"},"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 3 inbound Pith citation observations for arXiv:2210.01680."}