{"as_of":"2026-08-08T18:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e4ead3af712912c9d70983ffae5046189e634bc607e0454b6232ff2ba80efab3","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T19:41:10.835315Z","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":"2026-07-03T23:29:02.746515Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.00116","last_updated":"2024-07-02T06:51:09Z","snapshot_observed_at":"2026-07-06T18:38:42.333605Z","submitted_at":"2024-06-27T14:00:11Z","title":"Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges","version":2},"cited_work":{"arxiv_id":"2407.00116","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.00116","snapshot_observed_at":"2026-07-03T23:29:02.746515Z","title":"Generative AI for synthetic data across multiple medical modalities: A systematic review of recent developments and challenges","venue":null,"work_id":"ccae10d7-79f6-420a-aa01-b21a11c1499d","year":2024},"citing_paper":{"arxiv_id":"2605.19060","last_updated":"2026-05-18T19:30:19Z","snapshot_observed_at":"2026-07-06T23:29:52.061489Z","submitted_at":"2026-05-18T19:30:19Z","title":"LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-20T10:55:18.167419Z"},"links":{"cited_paper":"/paper/2407.00116","citing_paper":"/paper/2605.19060"},"observation_digest":"sha256:81d905789a90feb961825cbda87c747a17277d4738dbe6f86f92f6bd297af1ab","observation_id":"6ea2af2f-1993-4242-b001-7cb4cc5bcbde","resolution":{"observed_at":"2026-05-20T10:58:13.941076Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00116","last_updated":"2024-07-02T06:51:09Z","snapshot_observed_at":"2026-07-06T18:38:42.333605Z","submitted_at":"2024-06-27T14:00:11Z","title":"Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges","version":2},"cited_work":{"arxiv_id":"2407.00116","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.00116","snapshot_observed_at":"2026-07-03T23:29:02.746515Z","title":"Generative AI for synthetic data across multiple medical modalities: A systematic review of recent developments and challenges","venue":null,"work_id":"ccae10d7-79f6-420a-aa01-b21a11c1499d","year":2024},"citing_paper":{"arxiv_id":"2606.18354","last_updated":"2026-06-16T18:01:41Z","snapshot_observed_at":"2026-08-07T04:29:47.066495Z","submitted_at":"2026-06-16T18:01:41Z","title":"Structural MRI Synthesis for Alzheimer's Disease via Conditional Diffusion on Anatomical Masks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-26T22:12:46.169295Z"},"links":{"cited_paper":"/paper/2407.00116","citing_paper":"/paper/2606.18354"},"observation_digest":"sha256:caa5a76265c6b33a21988c82839f45a0933bccd4b6257a6b5b87e77420da0e8d","observation_id":"66ec9202-e89b-4fe0-8fb3-5a87670bedb3","resolution":{"observed_at":"2026-07-03T23:29:02.748373Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00116","last_updated":"2024-07-02T06:51:09Z","snapshot_observed_at":"2026-07-06T18:38:42.333605Z","submitted_at":"2024-06-27T14:00:11Z","title":"Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00116","snapshot_observed_at":"2026-08-07T19:41:10.835315Z","title":"Ibrahim, Y","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.05993","last_updated":"2026-08-06T13:04:42Z","snapshot_observed_at":"2026-08-08T18:16:23.727029Z","submitted_at":"2026-08-06T13:04:42Z","title":"Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T19:41:10.835315Z"},"links":{"cited_paper":"/paper/2407.00116","citing_paper":"/paper/2608.05993"},"observation_digest":"sha256:21fb50b5ee97d6ae634387ad4728fba41a1f3b98a86525886690e22595a97d96","observation_id":"ebbba384-1791-4550-a742-8e3b4440b999","resolution":{"observed_at":"2026-08-07T19:41:10.835315Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2407.00116/citation-record","integrity":"/paper/2407.00116/integrity","json":"/paper/2407.00116/citation-record.json","paper":"/paper/2407.00116"},"outbound":[],"paper":{"arxiv_id":"2407.00116","last_updated":"2024-07-02T06:51:09Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T18:38:42.333605Z","submitted_at":"2024-06-27T14:00:11Z","title":"Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.00116."}