{"as_of":"2026-08-15T05:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e60eb1ca3a2c62dbbb308e8e54ee470091b1499fdc10854b868238d01f389c0b","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":"2026-08-14T06:32:32.682623+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":"2026-08-11T04:19:38.843433Z","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":"2026-08-10T04:20:38.757473Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.08551","last_updated":"2025-03-11T15:39:43Z","snapshot_observed_at":"2026-08-07T17:12:36.923428Z","submitted_at":"2025-03-11T15:39:43Z","title":"Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs","version":1},"cited_work":{"arxiv_id":"2503.08551","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.08551","snapshot_observed_at":"2026-08-10T04:20:38.757473Z","title":"Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs","venue":"cs.AI","work_id":"4890e25c-13d7-4e38-bb92-a858d416f3eb","year":2025},"citing_paper":{"arxiv_id":"2608.06609","last_updated":"2026-08-10T10:47:12Z","snapshot_observed_at":"2026-08-13T23:40:51.501529Z","submitted_at":"2026-08-06T21:52:18Z","title":"Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T04:20:37.469039Z"},"links":{"cited_paper":"/paper/2503.08551","citing_paper":"/paper/2608.06609"},"observation_digest":"sha256:f02038462fc900e5bdd37e4fca419c58691af60a350665f5932ba85f8e50c715","observation_id":"59286acf-659a-4e39-959a-fb227d199fe2","resolution":{"observed_at":"2026-08-10T04:20:38.761407Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2503.08551","last_updated":"2025-03-11T15:39:43Z","snapshot_observed_at":"2026-08-07T17:12:36.923428Z","submitted_at":"2025-03-11T15:39:43Z","title":"Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.08551","snapshot_observed_at":"2026-08-11T04:19:38.843433Z","title":"Reasoning and Sampling-Augmented MCQ Difficulty Prediction via","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06609","last_updated":"2026-08-10T10:47:12Z","snapshot_observed_at":"2026-08-13T23:40:51.501529Z","submitted_at":"2026-08-06T21:52:18Z","title":"Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-11T04:19:38.843433Z"},"links":{"cited_paper":"/paper/2503.08551","citing_paper":"/paper/2608.06609"},"observation_digest":"sha256:65c928117d2a99b5b3d4ec81588ace04ad224c6f4a1f57f82bb6567750405179","observation_id":"c815bad0-4c4a-45bc-b613-872a3e36c03e","resolution":{"observed_at":"2026-08-11T04:19:38.843433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2503.08551/citation-record","integrity":"/paper/2503.08551/integrity","json":"/paper/2503.08551/citation-record.json","paper":"/paper/2503.08551"},"outbound":[],"paper":{"arxiv_id":"2503.08551","last_updated":"2025-03-11T15:39:43Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-07T17:12:36.923428Z","submitted_at":"2025-03-11T15:39:43Z","title":"Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs"},"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 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.08551."}