{"as_of":"2026-08-23T14:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e06deb3e7adebf897e6c115572cd43e1617ea1fc3b4484c495a4264be7e82487","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":"2026-08-23T06:30:58.430688+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":"2026-08-04T13:15:32.180689Z","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":"2026-07-12T01:18:31.194167Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2201.07587","last_updated":"2022-01-19T13:20:52Z","snapshot_observed_at":"2026-08-16T17:27:21.411931Z","submitted_at":"2022-01-19T13:20:52Z","title":"Inferring Astrophysics and Dark Matter Properties from 21cm Tomography using Deep Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.07587","snapshot_observed_at":"2026-08-04T13:15:32.180689Z","title":"Neutsch, C","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.01121","last_updated":"2026-06-03T17:40:08Z","snapshot_observed_at":"2026-08-13T02:37:27.272236Z","submitted_at":"2025-10-01T17:07:37Z","title":"CosmoUiT: A Vision Transformer-UNet Hybrid for Fast and Accurate Emulation of 21-cm Maps from the Epoch of Reionization","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-04T13:15:32.180689Z"},"links":{"cited_paper":"/paper/2201.07587","citing_paper":"/paper/2510.01121"},"observation_digest":"sha256:3258ed092cf695169efabf320591e061dfd658f280fb159084a87af8ed05918e","observation_id":"bf7e8ed7-62d8-4cf7-bfb2-4a30456fa3d3","resolution":{"observed_at":"2026-08-04T13:15:32.180689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.07587","last_updated":"2022-01-19T13:20:52Z","snapshot_observed_at":"2026-08-16T17:27:21.411931Z","submitted_at":"2022-01-19T13:20:52Z","title":"Inferring Astrophysics and Dark Matter Properties from 21cm Tomography using Deep Learning","version":1},"cited_work":{"arxiv_id":"2201.07587","doi":null,"metadata_source":"pith","pith_arxiv_id":"2201.07587","snapshot_observed_at":"2026-07-12T01:18:31.194167Z","title":"Inferring Astrophysics and Dark Matter Properties from 21cm Tomography using Deep Learning","venue":"astro-ph.CO","work_id":"570d9606-b04f-4f49-96a6-75ff98a5d9a8","year":2022},"citing_paper":{"arxiv_id":"2607.03606","last_updated":"2026-07-03T21:31:31Z","snapshot_observed_at":"2026-08-20T03:46:06.679669Z","submitted_at":"2026-07-03T21:31:31Z","title":"Machine Learning and the SKA for Cosmic Dawn and the Epoch of Reionization","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-07-12T01:14:24.457057Z"},"links":{"cited_paper":"/paper/2201.07587","citing_paper":"/paper/2607.03606"},"observation_digest":"sha256:67711dd3f8b9946ae7efa8269df63e0fc2095b91e3ea26fd8fb2fbbed2279461","observation_id":"3d4d348a-079c-4af8-bdd7-4e5a840aab39","resolution":{"observed_at":"2026-07-12T01:18:31.196587Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2201.07587/citation-record","integrity":"/paper/2201.07587/integrity","json":"/paper/2201.07587/citation-record.json","paper":"/paper/2201.07587"},"outbound":[],"paper":{"arxiv_id":"2201.07587","last_updated":"2022-01-19T13:20:52Z","latest_version":1,"primary_category":"astro-ph.CO","snapshot_observed_at":"2026-08-16T17:27:21.411931Z","submitted_at":"2022-01-19T13:20:52Z","title":"Inferring Astrophysics and Dark Matter Properties from 21cm Tomography using Deep Learning"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2201.07587."}