{"as_of":"2026-08-14T09:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1c9b0087bdbeeb9a1cb9a6d3f8b224d0d6582c9fbda6a8566b618e7a2636e5fc","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":"2026-08-11T22:21:35.060842Z","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":"2026-08-07T14:54:19.782894Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2309.15179","last_updated":"2024-10-08T06:41:10Z","snapshot_observed_at":"2026-08-13T10:04:27.873040Z","submitted_at":"2023-09-26T18:25:57Z","title":"ParamANN: A Neural Network to Estimate Cosmological Parameters for $\\Lambda$CDM Universe Using Hubble Measurements","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.15179","snapshot_observed_at":"2026-08-11T22:21:35.060842Z","title":"Pal and R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03547","last_updated":"2025-09-09T12:55:02Z","snapshot_observed_at":"2026-08-12T15:55:20.553754Z","submitted_at":"2024-12-04T18:45:30Z","title":"Learning from galactic rotation curves: a neural network approach","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T22:21:35.060842Z"},"links":{"cited_paper":"/paper/2309.15179","citing_paper":"/paper/2412.03547"},"observation_digest":"sha256:00cd53c37d555efd001dfb6662e3af654876c316696b117d356a794c8d0e42b1","observation_id":"15fd08f3-2e19-45fb-9600-02381d1d2643","resolution":{"observed_at":"2026-08-11T22:21:35.060842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.15179","last_updated":"2024-10-08T06:41:10Z","snapshot_observed_at":"2026-08-13T10:04:27.873040Z","submitted_at":"2023-09-26T18:25:57Z","title":"ParamANN: A Neural Network to Estimate Cosmological Parameters for $\\Lambda$CDM Universe Using Hubble Measurements","version":3},"cited_work":{"arxiv_id":"2309.15179","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.15179","snapshot_observed_at":"2026-08-07T14:54:19.782894Z","title":"ParamANN: A Neural Network to Estimate Cosmological Parameters for $\\Lambda$CDM Universe Using Hubble Measurements","venue":"astro-ph.CO","work_id":"a16b4b2e-6cf1-47ff-8508-b4ed52a6febe","year":2023},"citing_paper":{"arxiv_id":"2505.17205","last_updated":"2025-05-22T18:27:29Z","snapshot_observed_at":"2026-08-14T08:19:00.108506Z","submitted_at":"2025-05-22T18:27:29Z","title":"Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T14:54:17.725282Z"},"links":{"cited_paper":"/paper/2309.15179","citing_paper":"/paper/2505.17205"},"observation_digest":"sha256:f6b46084cac3ed3f1d896af1e75c72478612c2057dcfd97f4809bcf84c5a0817","observation_id":"bcbb9ae3-a9b2-44ea-877a-843d8e9cc152","resolution":{"observed_at":"2026-08-07T14:54:19.884383Z","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/2309.15179/citation-record","integrity":"/paper/2309.15179/integrity","json":"/paper/2309.15179/citation-record.json","paper":"/paper/2309.15179"},"outbound":[],"paper":{"arxiv_id":"2309.15179","last_updated":"2024-10-08T06:41:10Z","latest_version":3,"primary_category":"astro-ph.CO","snapshot_observed_at":"2026-08-13T10:04:27.873040Z","submitted_at":"2023-09-26T18:25:57Z","title":"ParamANN: A Neural Network to Estimate Cosmological Parameters for $\\Lambda$CDM Universe Using Hubble Measurements"},"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 2 inbound Pith citation observations for arXiv:2309.15179."}