{"as_of":"2026-08-15T17:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:20cc31367737e2c1533f4da95b0aa44090764cb6a027d18e65f70e609d256570","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:48:12.422253Z","state":"measured"},{"denominator":24,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":24,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:48:10.930680Z","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":"2026-08-07T00:48:12.543628Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"cited_work":{"arxiv_id":"2506.12719","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.12719","snapshot_observed_at":"2026-08-07T00:48:12.543628Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","venue":"eess.IV","work_id":"0a9f17cc-b9b5-4867-885f-8bf227a2ac6b","year":2025},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:10.930680Z"},"links":{"cited_paper":"/paper/2506.12719","citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:84a1146a13ce5c069a353651fa3aeb144667910cd426c11df2b771cafb798d28","observation_id":"2844e6fc-5d7e-4cab-8d34-59e0a8e5f999","resolution":{"observed_at":"2026-08-07T00:48:12.587749Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.12719/citation-record","integrity":"/paper/2506.12719/integrity","json":"/paper/2506.12719/citation-record.json","paper":"/paper/2506.12719"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:15.446244Z","title":"Models such as generative adversarial networks (GANs)","venue":null,"work_id":"14d0ca27-f548-4cc0-9bbe-25022bb0e739","year":null},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:10.769286Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:525eedee632a6887e05530b60c4e0754856207b6f9a259de0aeaf8413434d10b","observation_id":"c6abba1f-25f6-46ba-b24e-61a4148525da","resolution":{"observed_at":"2026-08-07T00:48:15.502592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:15.294824Z","title":null,"venue":null,"work_id":"c3285cdd-413f-45f3-8549-d608314f3348","year":null},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:10.817870Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:2ddb314c7f902b797f6dc33365b9cf3d938131fd0adc2d512b3c3202b7ec62d9","observation_id":"09b5e9b8-6cea-4738-b486-08ac8c5d6a8b","resolution":{"observed_at":"2026-08-07T00:48:15.336874Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"cited_work":{"arxiv_id":"2506.12719","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.12719","snapshot_observed_at":"2026-08-07T00:48:12.543628Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","venue":"eess.IV","work_id":"0a9f17cc-b9b5-4867-885f-8bf227a2ac6b","year":2025},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:10.930680Z"},"links":{"cited_paper":"/paper/2506.12719","citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:84a1146a13ce5c069a353651fa3aeb144667910cd426c11df2b771cafb798d28","observation_id":"2844e6fc-5d7e-4cab-8d34-59e0a8e5f999","resolution":{"observed_at":"2026-08-07T00:48:12.587749Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:15.128116Z","title":null,"venue":null,"work_id":"85edb28c-aff3-4753-9aaf-c75c3bef2042","year":null},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.014078Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:bafca64efedefb41ad59c91786acbf10c8db4338fa8aeeafeac70d9217ea358c","observation_id":"3016008e-4d41-4ff8-8729-7087c3562f75","resolution":{"observed_at":"2026-08-07T00:48:15.229022Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:14.953151Z","title":"Datasets We used the large-scale ABCD dataset (n=11,220) to train our 3D autoencoder","venue":null,"work_id":"a7f1b6b8-7891-4cac-8812-26930daeb59b","year":2000},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.092715Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:66cd465c6f6c5e9e94151806c681cdc09be3a0a6faa83bbc9e2e1a1b2bdbe8c7","observation_id":"84211144-dfa4-4048-8578-70d93e6b9f73","resolution":{"observed_at":"2026-08-07T00:48:15.029344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:14.702885Z","title":"In the future, our model will be widely applied to explore and validate biomarkers associated with various brain disorders","venue":null,"work_id":"70822baf-0a00-475f-85e5-5a2d5f419f2c","year":null},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.171826Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:8e8aac841b9123a74fff0253cbb739f3eabc730c829e27b302fa8463eb8de9ce","observation_id":"8d7e2f4e-b990-4450-bc82-6e3e3b8ba855","resolution":{"observed_at":"2026-08-07T00:48:14.809317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:14.521284Z","title":"Gray matters: Vit-gan framework for iden- tifying schizophrenia biomarkers linking structural mri and functional network connectivity,","venue":null,"work_id":"31af7e94-42e6-4cea-a69b-58e9929ff877","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.227951Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:c430bdce5d87f7cc3be50b12057477971a49fe506c519d8495f0230c8efd8f89","observation_id":"17fccd0a-77f4-4b61-a30d-072cd8bd5a08","resolution":{"observed_at":"2026-08-07T00:48:14.599208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:14.373224Z","title":"Generative adversar- ial nets,","venue":null,"work_id":"6857bf6e-b186-4f0d-9177-3abe47462961","year":2014},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.331961Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:a1b5cf9dafb74f30fe77ba32bff010d8fd955d4c1ccb08805a4556553a02af95","observation_id":"16c37291-5c2f-4080-bbb8-9ea2edc690b0","resolution":{"observed_at":"2026-08-07T00:48:14.409234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:11.443514Z","title":"Denoising diffusion probabilistic models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.443514Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:7792a6054f0ef358b42d5f6c04900c0af1c6b9050330a6d4a5c68efcababaf7a","observation_id":"b20a48bc-2637-4712-aa01-a287ca6f6827","resolution":{"observed_at":"2026-08-07T00:48:11.443514Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:14.228479Z","title":"Segmentation of pelvic structures in t2 mri via mr-to-ct synthesis,","venue":null,"work_id":"bd6492e6-40cf-4534-a6b6-3f0e74a65fdb","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.538230Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:4bfdc5107089153e4d02f6fca4380cc25befe2bce97cc7f14156238ecfce701f","observation_id":"0da452a5-88f3-46d7-a5b4-2e96984bd7a8","resolution":{"observed_at":"2026-08-07T00:48:14.285336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:14.047633Z","title":"Gan-based generation of realistic 3d volumetric data: A system- atic review and taxonomy,","venue":null,"work_id":"d6e57e42-c366-43f9-a2dd-c8c8f14b518a","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.629487Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:581470170311c56c8d2e89c650b7026088f07a0e35ee22adf6f7deccb4052f7b","observation_id":"c3fcdc32-de0b-41f6-86a3-26ce880513f8","resolution":{"observed_at":"2026-08-07T00:48:14.110167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:11.701348Z","title":"High-resolution im- age synthesis with latent diffusion models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.701348Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:c7311abc116442e03813a5325ffdf3c9b9684fffc225c1f95dda08d40bd97a66","observation_id":"c64ace21-4c1b-4feb-b317-62e3b2c03230","resolution":{"observed_at":"2026-08-07T00:48:11.701348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:13.929294Z","title":"Phy-diff: Physics-guided hourglass diffusion model for diffusion mri synthesis,","venue":null,"work_id":"83abb287-f67f-4459-82b1-4d8596c4a93e","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.783771Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:f343a60634a2e37133dc1e78425c4eef97bc1249cfd903f507e2f8b84f80b78f","observation_id":"ec738e9f-ee01-4245-9f38-12bc4725134d","resolution":{"observed_at":"2026-08-07T00:48:13.985405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:13.684862Z","title":"Brain imaging generation with latent diffusion mod- els,","venue":null,"work_id":"35675104-edb7-455e-8800-a93eaa87e9a2","year":2022},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.840602Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:ec24aa83fefd982de883927f4c13404994f3640edf7263f66a996077cf3b9704","observation_id":"c8167cf6-444b-413e-819b-2e4fef60cde2","resolution":{"observed_at":"2026-08-07T00:48:13.816292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:13.558887Z","title":"A survey of emerging applications of diffusion probabilistic models in mri,","venue":null,"work_id":"32986cea-97f0-48cb-a029-bd91c2c31def","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.910252Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:6f7346da710bd396ba34dc0a2f4f0eaffd20549307e290030ec364eb4c100bd5","observation_id":"7e2c277c-3f30-4610-9952-a4d775874e67","resolution":{"observed_at":"2026-08-07T00:48:13.629763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:13.375805Z","title":"A survey on generative diffusion models,","venue":null,"work_id":"ba7ce5c8-bf1d-4adb-ad53-4826089565c3","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:11.970605Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:996e4957a6d22c337bfac1d750e3d2839fa81669f54ed7eb8bf7d8e206d9dbf3","observation_id":"72ed0471-ab3b-4fbb-8a8a-1eddf517b5f3","resolution":{"observed_at":"2026-08-07T00:48:13.487681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-13T14:19:26.598265Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-07T00:48:12.038612Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:12.038612Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:9e85b30bd04a7263ea01d6573fa2b540e057da048a95a38307a6e8e5a7179e4d","observation_id":"cef8f07f-02e3-4f8d-9ff4-a946c8b0e443","resolution":{"observed_at":"2026-08-07T00:48:12.038612Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:13.209015Z","title":"Cola-diff: Conditional latent diffusion model for multi-modal mri synthesis,","venue":null,"work_id":"66274c13-30bd-4ce0-8c74-1a075d504a83","year":2023},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:12.101499Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:deb63b656d653b5ad9fba77608483807d8005cb06624d6fe6dc8f298fb79e859","observation_id":"e3798aee-9976-470e-8cb9-4e2414786b1c","resolution":{"observed_at":"2026-08-07T00:48:13.298641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:13.079997Z","title":"Adaptive latent dif- fusion model for 3d medical image to image transla- tion: Multi-modal magnetic resonance imaging study,","venue":null,"work_id":"ba92a74f-c853-43cf-90ed-b8310ce5d474","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:12.172626Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:e0d061fa658418c8c7f6c4c48b6c314df2c1ba9319886705c0e8499622ea2890","observation_id":"0af1b735-4b4c-4f15-9b41-5c879c953056","resolution":{"observed_at":"2026-08-07T00:48:13.135894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:12.943912Z","title":"Syn- thetic ct generation from mri using 3d transformer-based denoising diffusion model,","venue":null,"work_id":"b13ca34e-6ba8-4800-8827-e26f60e95a97","year":2024},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:12.238258Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:6908d1891b2bd4b3d300fb343356d689adea3d9dc703e7c01a2f9dc46efc46f1","observation_id":"874c012b-afd4-43a6-aff0-1d397cec4c3c","resolution":{"observed_at":"2026-08-07T00:48:12.991783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.04589","last_updated":"2024-05-29T09:41:05Z","snapshot_observed_at":"2026-08-14T11:11:15.880276Z","submitted_at":"2021-07-09T17:59:30Z","title":"ViTGAN: Training GANs with Vision Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.04589","snapshot_observed_at":"2026-08-07T00:48:12.291019Z","title":"Vitgan: Training gans with vision transformers,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:12.291019Z"},"links":{"cited_paper":"/paper/2107.04589","citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:ca6c45677754c208e31d91925eda8b3be0ca0312906cad19da4d97c4d7f1b2dc","observation_id":"20ca5c38-3321-49e0-9d59-5ca0d144b2a6","resolution":{"observed_at":"2026-08-07T00:48:12.291019Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:12.790571Z","title":"Schizophre- nia and cognitive dysmetria: a positron-emission to- mography study of dysfunctional prefrontal-thalamic- cerebellar circuitry.,","venue":null,"work_id":"66686a18-1587-4c5e-a86d-d1cc2ff7efb5","year":1996},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:12.358591Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:aab9fffb040915865bde632afdac9f26afbf7bac0238dbc39cf221db6d949339","observation_id":"1562fdb1-f1d7-4c14-9853-518462e1e4c8","resolution":{"observed_at":"2026-08-07T00:48:12.853413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:48:12.650594Z","title":"Structural analysis of the basal ganglia in schizophre- nia,","venue":null,"work_id":"ce0afdbf-3020-4a15-aec4-4d130dec0ccd","year":2007},"citing_paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:12.422253Z"},"links":{"citing_paper":"/paper/2506.12719"},"observation_digest":"sha256:64ad39a54b546db7ae9978d2c0889535c35bc84ebd8dffc2ba35caa386501e7c","observation_id":"ab7b2f03-44c0-4bd0-8ec2-a57b3fffcd01","resolution":{"observed_at":"2026-08-07T00:48:12.713967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.12719","last_updated":"2025-06-15T04:51:31Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-15T01:43:12.120531Z","submitted_at":"2025-06-15T04:51:31Z","title":"GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":1,"verified_fuzzy":16},"total_outbound_references":23},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2506.12719."}