{"as_of":"2026-08-08T06:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dd77b438ce0f7801deb9c24821782611741474b6d761b4d6e1ac702175bce192","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:58:19.631766Z","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":"2026-07-02T16:07:08.705454Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2209.13435","last_updated":"2023-02-23T13:31:20Z","snapshot_observed_at":"2026-08-08T04:01:12.255493Z","submitted_at":"2022-09-27T14:44:57Z","title":"Scaling Laws For Deep Learning Based Image Reconstruction","version":2},"cited_work":{"arxiv_id":"2209.13435","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.13435","snapshot_observed_at":"2026-07-02T16:07:08.705454Z","title":"Scaling laws for deep learning based image reconstruction","venue":null,"work_id":"378b95e0-8eb2-418b-a607-e1e79791bada","year":2023},"citing_paper":{"arxiv_id":"2211.01324","last_updated":"2023-03-14T00:22:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-11-02T17:43:04Z","title":"eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers","version":5},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-15T01:44:22.710205Z"},"links":{"cited_paper":"/paper/2209.13435","citing_paper":"/paper/2211.01324"},"observation_digest":"sha256:e8ac5a4c5fda3fc30901bf7cd26fcd37338f847018291bcaf948fdc8f1bbe7ef","observation_id":"911cff8d-3a9b-47b8-8d48-09344cc9fea7","resolution":{"observed_at":"2026-05-15T01:44:22.803125Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.13435","last_updated":"2023-02-23T13:31:20Z","snapshot_observed_at":"2026-08-08T04:01:12.255493Z","submitted_at":"2022-09-27T14:44:57Z","title":"Scaling Laws For Deep Learning Based Image Reconstruction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.13435","snapshot_observed_at":"2026-08-06T16:58:19.631766Z","title":"Scaling laws for deep learning based image reconstruction ,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12105","last_updated":"2025-07-16T10:21:45Z","snapshot_observed_at":"2026-08-06T16:51:20.329846Z","submitted_at":"2025-07-16T10:21:45Z","title":"Out-of-distribution data supervision towards biomedical semantic segmentation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T16:58:19.631766Z"},"links":{"cited_paper":"/paper/2209.13435","citing_paper":"/paper/2507.12105"},"observation_digest":"sha256:5fe2a529f514d3bda2acf57ddb274d000fe8f9336c80adfee74741e6c07cd13d","observation_id":"d939e652-1460-4bbf-b453-35302ef4c304","resolution":{"observed_at":"2026-08-06T16:58:19.631766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.13435","last_updated":"2023-02-23T13:31:20Z","snapshot_observed_at":"2026-08-08T04:01:12.255493Z","submitted_at":"2022-09-27T14:44:57Z","title":"Scaling Laws For Deep Learning Based Image Reconstruction","version":2},"cited_work":{"arxiv_id":"2209.13435","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.13435","snapshot_observed_at":"2026-07-02T16:07:08.705454Z","title":"Scaling laws for deep learning based image reconstruction","venue":null,"work_id":"378b95e0-8eb2-418b-a607-e1e79791bada","year":2023},"citing_paper":{"arxiv_id":"2509.24244","last_updated":"2026-05-11T07:55:31Z","snapshot_observed_at":"2026-07-06T22:31:00.843452Z","submitted_at":"2025-09-29T03:36:55Z","title":"Model Merging Scaling Laws in Large Language Models","version":4},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-18T13:32:33.009367Z"},"links":{"cited_paper":"/paper/2209.13435","citing_paper":"/paper/2509.24244"},"observation_digest":"sha256:2cf5f354adf2413867c170b8a64e7d15096cf9a914f9d43f1d9684057acb1d68","observation_id":"197baa68-5e81-45f7-a999-c5a90f07c46f","resolution":{"observed_at":"2026-05-18T13:32:37.803697Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.13435","last_updated":"2023-02-23T13:31:20Z","snapshot_observed_at":"2026-08-08T04:01:12.255493Z","submitted_at":"2022-09-27T14:44:57Z","title":"Scaling Laws For Deep Learning Based Image Reconstruction","version":2},"cited_work":{"arxiv_id":"2209.13435","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.13435","snapshot_observed_at":"2026-07-02T16:07:08.705454Z","title":"Scaling laws for deep learning based image reconstruction","venue":null,"work_id":"378b95e0-8eb2-418b-a607-e1e79791bada","year":2023},"citing_paper":{"arxiv_id":"2606.06725","last_updated":"2026-06-04T21:21:33Z","snapshot_observed_at":"2026-08-05T02:32:11.158017Z","submitted_at":"2026-06-04T21:21:33Z","title":"Compute-Optimal Network Design for Echocardiography Myocardial Segmentation and Perfusion Quantification using Neural Scaling Laws","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T23:02:38.001509Z"},"links":{"cited_paper":"/paper/2209.13435","citing_paper":"/paper/2606.06725"},"observation_digest":"sha256:4b4443fcc7a77a51c65665a5f9c098e0aae7da88b1fd47b1659acdc5db050a96","observation_id":"80a4729a-2e75-4b16-b37a-d01d49d63ffb","resolution":{"observed_at":"2026-07-02T16:07:08.706922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2209.13435/citation-record","integrity":"/paper/2209.13435/integrity","json":"/paper/2209.13435/citation-record.json","paper":"/paper/2209.13435"},"outbound":[],"paper":{"arxiv_id":"2209.13435","last_updated":"2023-02-23T13:31:20Z","latest_version":2,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-08T04:01:12.255493Z","submitted_at":"2022-09-27T14:44:57Z","title":"Scaling Laws For Deep Learning Based Image Reconstruction"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2209.13435."}