{"as_of":"2026-08-14T00:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:23ea538b174ef6304b0dde34b8fb141af03089c68a361981a2ea982d53062609","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":"2026-08-13T06:32:02.005865+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":"2026-08-12T18:48:42.398430Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T11:06:53.072075Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1906.06339","last_updated":"2019-09-19T14:50:25Z","snapshot_observed_at":"2026-08-10T15:42:00.336697Z","submitted_at":"2019-06-14T18:00:00Z","title":"An interpretable machine learning framework for dark matter halo formation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.06339","snapshot_observed_at":"2026-08-12T18:48:42.398430Z","title":"V., Pontzen, A., & Lochner, M","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2411.11280","last_updated":"2025-08-24T02:53:56Z","snapshot_observed_at":"2026-08-13T09:30:03.895326Z","submitted_at":"2024-11-18T04:44:37Z","title":"AI-Powered Reconstruction of Dark Matter Velocity Fields from Redshift-Space Halo Distribution","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T18:48:42.398430Z"},"links":{"cited_paper":"/paper/1906.06339","citing_paper":"/paper/2411.11280"},"observation_digest":"sha256:e069c8aff58201b6c06f32b15c6a40a2fd105ce49a40369ac8c8c9fd3070fb39","observation_id":"a00ffe78-5d92-4595-9af1-7a44f2b65cd3","resolution":{"observed_at":"2026-08-12T18:48:42.398430Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.06339","last_updated":"2019-09-19T14:50:25Z","snapshot_observed_at":"2026-08-10T15:42:00.336697Z","submitted_at":"2019-06-14T18:00:00Z","title":"An interpretable machine learning framework for dark matter halo formation","version":2},"cited_work":{"arxiv_id":"1906.06339","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1906.06339","snapshot_observed_at":"2026-07-02T11:06:53.072075Z","title":"Lucie-Smith, H.V","venue":null,"work_id":"fe2f2b97-1817-403a-8133-9b8867e930d4","year":2019},"citing_paper":{"arxiv_id":"2508.00049","last_updated":"2025-11-26T16:49:35Z","snapshot_observed_at":"2026-08-03T20:51:11.519678Z","submitted_at":"2025-07-31T17:59:44Z","title":"Segmenting proto-halos with vision transformers","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-19T01:43:50.077818Z"},"links":{"cited_paper":"/paper/1906.06339","citing_paper":"/paper/2508.00049"},"observation_digest":"sha256:7cf279342ca152eec8b65aca13802c02b9732c0ebe910c677930750663217c05","observation_id":"e3446f8f-e2ea-40a3-8bc2-a90466a6cd20","resolution":{"observed_at":"2026-05-19T01:46:58.007779Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.06339","last_updated":"2019-09-19T14:50:25Z","snapshot_observed_at":"2026-08-10T15:42:00.336697Z","submitted_at":"2019-06-14T18:00:00Z","title":"An interpretable machine learning framework for dark matter halo formation","version":2},"cited_work":{"arxiv_id":"1906.06339","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1906.06339","snapshot_observed_at":"2026-07-02T11:06:53.072075Z","title":"Lucie-Smith, H.V","venue":null,"work_id":"fe2f2b97-1817-403a-8133-9b8867e930d4","year":2019},"citing_paper":{"arxiv_id":"2606.05047","last_updated":"2026-06-03T16:07:40Z","snapshot_observed_at":"2026-08-09T15:46:32.525915Z","submitted_at":"2026-06-03T16:07:40Z","title":"Full Nonlinear Velocity Reconstruction With Transformer and Ensemble Tree Machine Learning","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-06-28T04:42:25.089569Z"},"links":{"cited_paper":"/paper/1906.06339","citing_paper":"/paper/2606.05047"},"observation_digest":"sha256:b032388a7e3978c3582d3fb32c0b03ed539fb023d58590893de936561461759a","observation_id":"2e4b72e0-5bf3-445b-8885-9409fddc396b","resolution":{"observed_at":"2026-07-02T11:06:53.073443Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1906.06339/citation-record","integrity":"/paper/1906.06339/integrity","json":"/paper/1906.06339/citation-record.json","paper":"/paper/1906.06339"},"outbound":[],"paper":{"arxiv_id":"1906.06339","last_updated":"2019-09-19T14:50:25Z","latest_version":2,"primary_category":"astro-ph.CO","snapshot_observed_at":"2026-08-10T15:42:00.336697Z","submitted_at":"2019-06-14T18:00:00Z","title":"An interpretable machine learning framework for dark matter halo formation"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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:1906.06339."}