{"as_of":"2026-08-10T00:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fd14a0e93abb36d1bbd72f900c8ab477f2bcc871bf0548efc373539b1d987f13","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":"2026-08-05T22:06:28.302417Z","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":"2026-08-09T06:31:02.800959+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":"2026-08-01T10:18:18.246169Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.07548","snapshot_observed_at":"2026-08-01T10:18:18.246169Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20311","last_updated":"2026-07-22T15:57:48Z","snapshot_observed_at":"2026-08-07T20:24:22.590717Z","submitted_at":"2026-07-22T15:57:48Z","title":"Quantum-state block texture and its quantification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T10:18:18.246169Z"},"links":{"cited_paper":"/paper/2508.07548","citing_paper":"/paper/2607.20311"},"observation_digest":"sha256:a8a1da36aa7c3c30de3b5a3925352361bc0994409246b03ffbc6cb71cf0a9537","observation_id":"323d92ad-4fd0-46b9-9ea2-4315b6d4a456","resolution":{"observed_at":"2026-08-01T10:18:18.246169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2508.07548/citation-record","integrity":"/paper/2508.07548/integrity","json":"/paper/2508.07548/citation-record.json","paper":"/paper/2508.07548"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:06:31.859110Z","title":"Physics in Medicine & Biology 58(13), R97 (2013)","venue":null,"work_id":"90b3602b-7942-4fc9-84f1-d5a12e27045c","year":2013},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:26.779262Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:d680aa83a4ab99857adb78182bdde7f5cf6edfd493b29bb5c4c2020cf8905eba","observation_id":"2ab05211-3a4d-41ee-94f4-1459f17a2692","resolution":{"observed_at":"2026-08-05T22:06:31.862536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:31.847904Z","title":"In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVMI)","venue":null,"work_id":"143f396e-b3a9-4b57-b5dc-0a426f58ed95","year":2016},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:26.819807Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:8f4df5a4ba09b68d57708f7a9d5edb41501e89ac38df33d490bb0415e829aefc","observation_id":"69f03f3a-eca4-46f6-9446-c30de9371145","resolution":{"observed_at":"2026-08-05T22:06:31.851736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:31.836847Z","title":"In: MICCAI","venue":null,"work_id":"2caa1945-5ef9-48a2-a1a3-58d42cc0e53f","year":2016},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:26.878849Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:d6b5874750e21e335bd3caf6c7f526200c3fc60fa8eb68abb08692d01688ce9e","observation_id":"f96840c3-1ed8-42b8-9e7f-9db5e5a583e0","resolution":{"observed_at":"2026-08-05T22:06:31.840239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:31.826018Z","title":"In: Proceed- ings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining","venue":null,"work_id":"9e427587-48ca-42f1-b009-b5f200f0a4f4","year":2008},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:26.966698Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:bf9894edd9bde45f63fc3b364b178dca57a6eabbf82b7489943412c46dad0f09","observation_id":"2b6e31c0-c6bd-44c5-bb5d-c23deec46026","resolution":{"observed_at":"2026-08-05T22:06:31.829550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:31.690078Z","title":"In: International Conference on Medical Image Computing and Computer- Assisted Intervention","venue":null,"work_id":"a4a37b55-77ae-4567-bbbc-b457044afa7a","year":2021},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.057994Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:4fe34394f67ef1abe8d7d50a9e0b0be1b8f7b6ac6c2f5dce353b474a135a7890","observation_id":"d8d5782d-0fc7-4e3a-89fc-f3c4616b3930","resolution":{"observed_at":"2026-08-05T22:06:31.803825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:31.455485Z","title":"In: ISBI (2019)","venue":null,"work_id":"1985fe69-3770-4aae-891d-760504bb5151","year":2019},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.115847Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:59eb29fa96756d27417e2727534dbfa2419acb872aaa076d8764ca659ac13024","observation_id":"0740d021-08bd-420d-84f3-a12a987dc430","resolution":{"observed_at":"2026-08-05T22:06:31.570519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:31.240571Z","title":"In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","venue":null,"work_id":"96631b50-86b8-4ff6-b993-72c43dd7abfc","year":2021},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.205509Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:7b846dfe87468b038bbd2000ed3fa2f1e9b44af3be5b5e275d36d02de85f89ee","observation_id":"4c63dbe1-6beb-4f74-bd78-36b55f0c6e1f","resolution":{"observed_at":"2026-08-05T22:06:31.334814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:31.054663Z","title":"In: Guyon, I., Luxburg, U.V ., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R","venue":null,"work_id":"65d715cb-f832-4d5a-bee9-d4b5ca6733ec","year":2017},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.342788Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:ba5455f30b77747e0a95b4da4b9f7833a9d740c04fbea72ff33bb812430b595e","observation_id":"55e96cbc-a1e2-48c6-888c-44ead0a36db7","resolution":{"observed_at":"2026-08-05T22:06:31.151865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:30.838923Z","title":"In: Workshop on challenges in representation learning, International Conference on Machine Learning","venue":null,"work_id":"3109b7c9-7d72-4de0-9f9c-d14358a62868","year":2013},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.400703Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:71b383202770f937d1dda487384426616eda4c8059dab1abccb3bacee0a71985","observation_id":"e904685a-eeaf-47f9-9ca6-bfa05a2cae92","resolution":{"observed_at":"2026-08-05T22:06:30.933960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:30.598037Z","title":"Physics in Medicine & Biology 54(19), R59 (2009)","venue":null,"work_id":"9addb613-db27-4d4c-9498-d5a0e26aacfc","year":2009},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.432224Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:de55c65c0290c00c325241cec115f8ed189d36e94d23a81eddfec60535ac5fe8","observation_id":"bfe22229-ebff-4a41-a47c-2841bd5c7227","resolution":{"observed_at":"2026-08-05T22:06:30.741914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:30.360901Z","title":"IEEE Journal of Biomedical and Health Informatics 26(9), 4623–4634 (2022)","venue":null,"work_id":"8a45da4c-b3ae-46d2-b1ea-23fee00f63df","year":2022},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.491624Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:db7c8c82dfe1b3b93f7705e1f6871b776bb1b84faf0e226577ef8711ec334c54","observation_id":"e4ab922e-0a4b-4280-b9d7-ce0effa58bc6","resolution":{"observed_at":"2026-08-05T22:06:30.470621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:30.113790Z","title":"Nature medicine 26(6), 900–908 (2020)","venue":null,"work_id":"8e179223-692c-4b9c-a390-9c1f0d2ba02b","year":2020},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.547555Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:aef954adc3a4f2ecd604fc0f9c35643b5072b34a6c3b9997a8dede976feb24fd","observation_id":"29c83235-e188-4a9b-a8c6-edc549c1f2d1","resolution":{"observed_at":"2026-08-05T22:06:30.239063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:29.786953Z","title":"IEEE Transactions on Medical Imaging (2023)","venue":null,"work_id":"0dccef76-ec6b-4b52-b944-62d569c11e11","year":2023},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.614664Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:81825381cd84ce9c66092aec89c0f8a3d1d4635fc7e553f950dfdc08208a9491","observation_id":"f16f4836-905b-44b3-9300-6c4b18100ee5","resolution":{"observed_at":"2026-08-05T22:06:29.908834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:29.614753Z","title":"In: International Conference on Medical Image Computing and Computer- Assisted Intervention","venue":null,"work_id":"55267607-b299-47eb-a5a8-e55d020bc5f6","year":2019},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.669549Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:2081f01c696d86cffe4a22b3f517f79734a4eccc05d7084a35f709ccef411b55","observation_id":"f288d5a5-241f-4a06-b5c2-278366f235e9","resolution":{"observed_at":"2026-08-05T22:06:29.690661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05278","last_updated":"2020-07-06T17:38:19Z","snapshot_observed_at":"2026-08-07T18:58:50.982040Z","submitted_at":"2020-06-09T14:08:03Z","title":"An Overview of Deep Semi-Supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.05278","snapshot_observed_at":"2026-08-05T22:06:27.723938Z","title":"arXiv preprint arXiv:2006.05278 (2020)","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.723938Z"},"links":{"cited_paper":"/paper/2006.05278","citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:3431eb47721fdf7392ff2caa7b2e9c78d382cf890e2b88aced60bd5c6cb9fa29","observation_id":"1bfd658a-5226-4242-a1bc-05776c9f7634","resolution":{"observed_at":"2026-08-05T22:06:27.723938Z","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":"2026-08-05T22:06:29.506933Z","title":"Investigative Ophthalmology & Visual Science 50(5), 2004–2010 (2009)","venue":null,"work_id":"38028816-58fe-4bf0-aba2-b38a5fabbd10","year":2004},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.816275Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:e32b4ad17767b28e788cf9f5a95a18e5d395baeb0af0e97ec2d900578e32683e","observation_id":"9eb2308c-95d2-4c22-a7c2-748b5ef357b5","resolution":{"observed_at":"2026-08-05T22:06:29.559036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:29.338851Z","title":"Yamane et al","venue":null,"work_id":"ccfd369b-5542-4fd0-84d4-a84b0f74b3ef","year":2023},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.873147Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:12768edca1a89c1a06428c71578bc7c83dae93efef67ad67b21d31c7b863383b","observation_id":"808095ad-5c6f-4d53-af84-cf730902ef21","resolution":{"observed_at":"2026-08-05T22:06:29.401720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:29.147588Z","title":"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelli- gence and Lecture Notes in Bioinformatics) 9351, 234–241 (2015)","venue":null,"work_id":"b81dfc78-893c-45c7-a5ee-704d004ee6f1","year":2015},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.932359Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:c5dbabfbc004eec512955828a6132b24767ceb0721e0249c6fca56f5c7e2476a","observation_id":"0d66b889-3f90-458c-94ed-b4ae7df862bf","resolution":{"observed_at":"2026-08-05T22:06:29.242452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:28.988781Z","title":"Medical image analysis13(5), 701–714 (2009)","venue":null,"work_id":"988d362f-6377-457e-8937-37360c5baa78","year":2009},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:27.993642Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:c7c47b4a7c99d415bf3b8f4021490184b4ad3edfc25a8a7f4f2f33330bd95b96","observation_id":"644bd27b-027d-4f0a-8516-10a6759290a4","resolution":{"observed_at":"2026-08-05T22:06:29.064040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:28.843738Z","title":"IEEE Trans- actions on Medical Imaging 23(4), 501–509 (2004)","venue":null,"work_id":"237fa07e-eeaf-4b4a-bd44-e68aea4d9eec","year":2004},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:28.084198Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:44c9179c4b7d463319d22469a44a3241e1b647c3804dbc96fb2e29ce0e5009b7","observation_id":"bf457b09-6888-4a8b-bd2c-da2e719c240f","resolution":{"observed_at":"2026-08-05T22:06:28.893136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:28.702711Z","title":"Machine learning 109(2), 373–440 (2020)","venue":null,"work_id":"286761af-c8c2-4417-b4be-47b5598cf42b","year":2020},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:28.171135Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:9e6cc02053d6e4f46456b813654a87f2b70ac15fe7eeed8799b3eb1bf7052302","observation_id":"c849747a-402a-4f72-8d63-f0425ca7b8c2","resolution":{"observed_at":"2026-08-05T22:06:28.762975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:28.552529Z","title":"Annals of the BMV A2013(7), 1–22 (2013)","venue":null,"work_id":"23a975c2-e629-40f9-b735-2b4ef4a49447","year":2013},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:28.233536Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:d46a84ff9873c37d1fd60ed6ef670365a957f201df44313a09b64c46ccf80c37","observation_id":"6cd946d1-ccb0-4f2f-bd7a-439ac7368ecd","resolution":{"observed_at":"2026-08-05T22:06:28.629983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T22:06:28.401046Z","title":"In: International Conference on Medical Image Computing and Computer-Assisted Intervention","venue":null,"work_id":"8eb8d758-f603-4d9c-a08b-2befeff6a251","year":2021},"citing_paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T22:06:28.302417Z"},"links":{"citing_paper":"/paper/2508.07548"},"observation_digest":"sha256:1f65538a605a4248b953bc302443c1943d724d4a01c0aa404edc203d94f30ef7","observation_id":"cd49b7f4-f1e0-4146-94c6-4f8335d4949c","resolution":{"observed_at":"2026-08-05T22:06:28.459307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.07548","last_updated":"2025-08-11T02:11:49Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T22:06:26.440275Z","submitted_at":"2025-08-11T02:11:49Z","title":"Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":22},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2508.07548."}