{"as_of":"2026-08-22T14:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:246b25d129aa8192f58075ad57701bcd420c84fe2388fa200024fff70b486375","coverage":[{"denominator":19,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-30T01:09:27.569795Z","state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.28513/citation-record","integrity":"/paper/2606.28513/integrity","json":"/paper/2606.28513/citation-record.json","paper":"/paper/2606.28513"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:90c730732ddf227653619caf49018f07310b7dc783be53acefbaa911698a0389","observation_id":"8b28c322-0ae8-4e5f-b153-cdbaf29f3936","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:51ba380a1b98ce721758006da735493ff886aaaa7f08fa202fc7ca446836444e","observation_id":"d7f09ad5-6232-44bc-9bb4-9e65edaeaa71","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.10541","last_updated":"2021-03-18T21:51:58Z","snapshot_observed_at":"2026-08-16T18:37:52.721394Z","submitted_at":"2021-03-18T21:51:58Z","title":"Quantitative investigation of low-dose PET imaging and post-reconstruction smoothing","version":1},"cited_work":{"arxiv_id":"2103.10541","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2103.10541","snapshot_observed_at":"2026-07-03T04:27:36.938043Z","title":"arXiv preprint arXiv:2103.10541","venue":null,"work_id":"ae77912b-a810-44cd-8584-b5e5293eb6dc","year":2021},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"cited_paper":"/paper/2103.10541","citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:91ef76d672cc8631e1827a60605f896f3c8572e9742c69b108cf26a74e041837","observation_id":"68b798d1-b53b-4524-9cc4-4e108aba7013","resolution":{"observed_at":"2026-07-01T15:45:48.454372Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:d3500f972bd86e7de74954969e0e9917031334a38fe83f91c4465b07fcff5957","observation_id":"548f2075-8e2d-4e21-8436-faa70725357b","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":"Turku PET Centre Modelling Report (2003)","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:bd6afaa4941f181f954ede51425f6f61f89d0c9d985cc6a450df57370fcb213f","observation_id":"edcd7481-ccf0-40bf-80d0-26cb8c0da88a","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":"IEEE Trans","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:d9d0ca6d75b2b4f3c43ce8940459f639405e67881970a34b37a342819591ebe0","observation_id":"7ea4caf2-0bad-4327-ba28-7dc88051e4ca","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:9a084285a6404f9ddd396373bb382f57e462ca5e4142012b1d27399ff80b8e38","observation_id":"f0047181-0202-45ef-bf3b-635dcc6ad97f","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:21ed6c649bd703ecafc9a4a2a55bee21712e9c59df543c031570206259780e7d","observation_id":"fcc69cd8-a1db-4f81-b328-f32e94887241","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:284348b14a458afe80ab6d05ba90dbc914c315091b987134e91254a0c4fe08d9","observation_id":"02bf3bb5-2281-4d3f-94a6-ce2372651c65","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:a98ed31167c127c70a8ada7a39ac9786d98060dffa0730a9bb8cd8878afaecfe","observation_id":"36e346ed-de2e-4734-9ab1-00dbaec803cc","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12996","last_updated":"2025-06-16T23:04:59Z","snapshot_observed_at":"2026-08-21T07:57:13.985025Z","submitted_at":"2024-05-02T20:55:07Z","title":"Dose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data","version":3},"cited_work":{"arxiv_id":"2405.12996","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.12996","snapshot_observed_at":"2026-07-01T15:45:48.455542Z","title":"arXiv:2405.12996 (2024)","venue":null,"work_id":"0445210e-691a-4429-89d3-69c5becfba0e","year":2024},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"cited_paper":"/paper/2405.12996","citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:ae32d4c0e970ca4423430b482fa8926c1140ce60e807481e96c93d3b18ead57b","observation_id":"6bd514c6-2a0e-4ab5-b0ca-05b7dc0a461d","resolution":{"observed_at":"2026-07-01T15:45:48.457405Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.08034","last_updated":"2022-03-15T16:15:24Z","snapshot_observed_at":"2026-08-20T12:08:13.243393Z","submitted_at":"2022-03-15T16:15:24Z","title":"A Noise-level-aware Framework for PET Image Denoising","version":1},"cited_work":{"arxiv_id":"2203.08034","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.08034","snapshot_observed_at":"2026-07-01T15:45:48.466886Z","title":"arXiv:2203.08034 (2022)","venue":null,"work_id":"a124dba7-6a50-41c1-9cd0-158d0a7fb592","year":2022},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"cited_paper":"/paper/2203.08034","citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:cb3a9b2b1dde7d3985a01c65c35a6cc7097e76e53c704340e6ee06b0559344e4","observation_id":"024bffa9-ca87-4967-a280-555dacd939b9","resolution":{"observed_at":"2026-07-01T15:45:48.479289Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-06-30T01:09:27.569795Z","title":"IEEE Trans","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:1e87f790a5b0244b7fbf48ab2af9cbf11ee3ceb528cc987796dcb00df53b3ce7","observation_id":"bd7ce173-019a-40ed-a1c5-86cac9b8ac0d","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:28ca70d87e73b6dc3899a5d56bd1085eb15513175e657f92602f72a9e2d47d3d","observation_id":"918cd18a-5f00-4453-b496-0190244fd684","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:ae1ca61be7b151a30a7ccc13a9a6716229a3fcb3ab5cdcf04ce9b8ddfefd448e","observation_id":"27ef55e8-2f62-4d07-ab44-42a61e6f30c5","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":"In: International Con- ference on Learning Representations (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:6f5e4a137926ec5bc67476db5c30e914fcba1cf857e501cd03d42a9eea9d0705","observation_id":"f0245a95-6a13-42af-8838-a1d97ef026c4","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":"and Shi, K., 2025, September","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:842e5225c3245b54980ad10eed24d38fe779a221d905a45587497f6f7e8f3a68","observation_id":"07f9d9ac-7760-4f0c-a99f-08601531b29a","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":"In: MICCAI 2015, LNCS 9351, pp","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:219297811cc4f65e9e276bdf37293b2806b698345874c86da3fb8305d397040e","observation_id":"fdb5eb66-5dcb-4e68-b72f-eaf7a0b170e4","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T01:09:27.569795Z","title":"-Y., Zhou, T., Efros, A.A.: Image -to-Image Translation with Conditional Adversarial Networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T01:09:27.569795Z"},"links":{"citing_paper":"/paper/2606.28513"},"observation_digest":"sha256:22d6afd16b8036f4416ecd365e9fbfdbee368b2e372beefdc811a8f8ee47a912","observation_id":"a368c748-99eb-47ef-9472-ae7110d7da91","resolution":{"observed_at":"2026-06-30T01:09:27.569795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.28513","last_updated":"2026-06-26T18:09:04Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-20T04:15:10.167679Z","submitted_at":"2026-06-26T18:09:04Z","title":"HDDPM: Heteroscedastic Denoising Diffusion Probabilistic Model for Quantitative Low-Count Brain PET Recovery"},"reference_resolution":{"displayed":19,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":19},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2606.28513."}