{"as_of":"2026-08-21T20:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c0a66001313bae28e802db5f314153b3f17f6c44ff7c9dcf650ede1c12154818","coverage":[{"denominator":20,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":20,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T23:44:41.426881Z","state":"measured"},{"denominator":20,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":20,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2412.20007/citation-record","integrity":"/paper/2412.20007/integrity","json":"/paper/2412.20007/citation-record.json","paper":"/paper/2412.20007"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:44:41.764445Z","title":"Skin cancer facts page,","venue":null,"work_id":"025ab597-d7d7-428f-9bfa-787ff8dedd61","year":2024},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.329941Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:ec1c66355111c28bab1567f4a518680c88e2fe7dc5ba1c4f5f3e6c3d99ac4be2","observation_id":"733b8ca2-61c4-49e9-8769-227c47729fbc","resolution":{"observed_at":"2026-08-10T23:44:41.769918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.747514Z","title":"Skin cancer facts page,","venue":null,"work_id":"23d2f792-bd00-4327-81c3-d6d9996436c0","year":2022},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.335284Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:e55024c4c7974ab6fffb24fc3293b1ec81153d30232f0d9256a4e1152afb7c66","observation_id":"83718d8c-b213-4642-8d4a-b261357fa69b","resolution":{"observed_at":"2026-08-10T23:44:41.752724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.731622Z","title":"Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities,","venue":null,"work_id":"8732daf5-fba7-4e94-82fe-9d579d762b2e","year":2020},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.340717Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:0ba0199b78882c64fb76c2402092db8d68d7911b07e70a2ad8751bf025649a0d","observation_id":"00cff760-4164-400e-aba6-5124cce0c5e9","resolution":{"observed_at":"2026-08-10T23:44:41.736599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.715569Z","title":"Current applications and future impact of machine learning in radiology,","venue":null,"work_id":"fecbc101-6693-4186-b2df-1ba91140ef2c","year":2018},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.346008Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:ec8d17e2b3cde4ed59c52c5da7536f7ac7354bbd92b7b0d35c2cd790ac01cc41","observation_id":"f0e2dfa1-3c53-4d7c-989a-bbb9f1a4cbf6","resolution":{"observed_at":"2026-08-10T23:44:41.720600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.698885Z","title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning,","venue":null,"work_id":"60dc6d4c-ec0d-4747-9712-8e3ff1f6e75c","year":2016},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.351144Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:824dedeafa3a9f14360af91249a846db631c0649dbdf674fcbb5daa500cb2967","observation_id":"df158a08-cfcd-431f-b900-d668ae0fa653","resolution":{"observed_at":"2026-08-10T23:44:41.704037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.683397Z","title":"Bayesian neural networks,","venue":null,"work_id":"7b6819a3-25c5-43b4-8e48-b39a55cb9781","year":1997},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.357100Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:eea4ef51655bd4620ca5e10ee8dae05e82a0adafca6b9a2681afee46015a2cc3","observation_id":"5c80b00a-daaa-424a-8d08-20959de83693","resolution":{"observed_at":"2026-08-10T23:44:41.688334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.363166Z","title":"The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.363166Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:92fcf7313eb84b7c8695dbb74011c57048c0435ce35929bd88d74bc678135957","observation_id":"d6892960-e80d-43e8-b7fa-d97004868da5","resolution":{"observed_at":"2026-08-10T23:44:41.363166Z","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":"2026-08-10T23:44:41.656993Z","title":"Bayesian neural networks for uncertainty estimation of imaging biomarkers,","venue":null,"work_id":"8e260934-65dc-472c-a3bf-68ec642a5099","year":2020},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.368089Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:4fb1bd58c95b9804dbd771a67dcf4efb3596a133b7b24047ab7e158b9cde4400","observation_id":"844c779b-a119-49ce-bbec-d1ff95d358d5","resolution":{"observed_at":"2026-08-10T23:44:41.662018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.641272Z","title":"An exploration of un- certainty information for segmentation quality assessment,","venue":null,"work_id":"6f78af29-deb3-4425-9041-1bcee7d9457f","year":2020},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.372891Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:a1b46608aa892dcfbcf93afc707c26895eeefd23f2b01d4331efbee6e09220ec","observation_id":"30aee9c5-92bd-431c-a40a-5946dbb9bc9c","resolution":{"observed_at":"2026-08-10T23:44:41.646249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.625071Z","title":"Accuracy, uncertainty, and adaptability of automatic myocardial asl segmentation using deep cnn,","venue":null,"work_id":"85581e4c-d98f-4e69-a55f-effc470fc7c7","year":2020},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.377691Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:490352e19796e93e42cb36daccd2b09fe840bda5c186c0d67ee0f95a9e5635c5","observation_id":"2f304a55-e0a0-4719-a3a9-beec4e588c2d","resolution":{"observed_at":"2026-08-10T23:44:41.629919Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.609827Z","title":"Quantifying uncer- tainty of deep neural networks in skin lesion classification,","venue":null,"work_id":"3d37aa30-a2e7-4215-b86d-095344e2d65d","year":2019},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.382528Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:90147fc1c8fc78194bbba269b9cd6c50dae698f693710cab748bf70c03c37e1e","observation_id":"946a2431-1a19-4373-81d8-98331bdf04e9","resolution":{"observed_at":"2026-08-10T23:44:41.614798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.594659Z","title":"Un- certainty estimation in deep neural networks for dermoscopic image classification,","venue":null,"work_id":"4a6e8877-70ff-4231-996b-1f3ce0339c79","year":2020},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.387501Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:4d05ba7790f5423c124b11859f327a46dd0f720465e574c47af06f28b714ad68","observation_id":"636bffbf-67d2-4919-a06d-38776d1fbc7d","resolution":{"observed_at":"2026-08-10T23:44:41.599476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.577370Z","title":"Multi- class skin cancer classification architecture based on deep convolutional neural network,","venue":null,"work_id":"737c3b9d-a280-4e4c-95b6-6267b2d422aa","year":2023},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.392725Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:325de7fe10d154c11096751d7936245a56a0040263d22b165ed2a1c15c6b5309","observation_id":"804badb2-8c3f-4fb4-ab2f-1a10fb693fa8","resolution":{"observed_at":"2026-08-10T23:44:41.583036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.560064Z","title":"Melanoma segmentation using deep learning with test-time augmenta- tions and conditional random fields,","venue":null,"work_id":"39fcb894-ba19-4558-a1cf-5095f3456e9d","year":2022},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.397267Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:e378e7ae500594bc2fd2dfb79fc1204aaadb5dc2b461042fdbcb864c6e189d0c","observation_id":"f4986990-bd96-4f88-ac89-e2d1febc3f46","resolution":{"observed_at":"2026-08-10T23:44:41.565245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.543586Z","title":"Skin lesion seg- mentation using deep learning for images acquired from smartphones,","venue":null,"work_id":"de3b1d25-8184-487a-a65b-434e12c33d82","year":2019},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.402188Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:870cf638d4b6d360c0dcf39c6ac123316cd1a831fd42555c4d9978fb5639e432","observation_id":"a27d44bc-61f0-47ad-9476-ceb76b8380e8","resolution":{"observed_at":"2026-08-10T23:44:41.549209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.526840Z","title":"Melanoma segmentation: A framework of im- proved densenet77 and unet convolutional neural network,","venue":null,"work_id":"730f7816-e148-44b1-a296-e2c811bcef51","year":2022},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.407161Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:7e8cdc8756281f2e9f127d44c3fe460cdff365e7efed8c90571e919b47c182f5","observation_id":"df9e80da-8264-4f93-b6e6-0ddbc67de253","resolution":{"observed_at":"2026-08-10T23:44:41.531954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-10T23:44:41.511174Z","title":"ISIC Archive homepage,","venue":null,"work_id":"72f0b080-4693-4c18-9b10-8e8cb93e4612","year":2019},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.412140Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:77eef9371e61d2bdb9f11c5dbf3562e6a6fb7c1ffb00ae968a101730e97db103","observation_id":"94939e87-d88a-45d4-99b5-d864d5eec0dc","resolution":{"observed_at":"2026-08-10T23:44:41.516097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.02288","last_updated":"2019-08-30T09:42:42Z","snapshot_observed_at":"2026-08-19T10:57:03.612782Z","submitted_at":"2019-08-06T11:16:07Z","title":"BCN20000: Dermoscopic Lesions in the Wild","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.02288","snapshot_observed_at":"2026-08-10T23:44:41.416865Z","title":"Bcn20000: Dermoscopic lesions in the wild,","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.416865Z"},"links":{"cited_paper":"/paper/1908.02288","citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:74d01cbe82d741acf23b729ca7bb7f5279b93ff3e30d9b624c2072604139088a","observation_id":"09025622-c807-4cfd-96a2-d15b6025a6b8","resolution":{"observed_at":"2026-08-10T23:44:41.416865Z","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":"2026-08-10T23:44:41.492443Z","title":"A deep-learning toolkit for visualization and interpretation of segmented medical images,","venue":null,"work_id":"dbc1f9d4-ff0c-4ed2-b4f6-dce43563d03f","year":2021},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.422074Z"},"links":{"citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:2461a614ff79ad6ef06dd049639a18be035ca9100ef3be5b08a1fb3c5fe62275","observation_id":"4d2238cc-b345-42bb-a585-c5209c8057f0","resolution":{"observed_at":"2026-08-10T23:44:41.499864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-17T19:17:06.411141Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-10T23:44:41.426881Z","title":"Very deep convolutional networks for large-scale image recognition,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:41.426881Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2412.20007"},"observation_digest":"sha256:43ce3b96368ced3bb2e381ff682516fb2daac116763a19ec8d502ab377707201","observation_id":"e55a8115-3bcc-475d-a4e7-c12402a8a48f","resolution":{"observed_at":"2026-08-10T23:44:41.426881Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.20007","last_updated":"2024-12-28T04:06:44Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-17T06:46:05.888478Z","submitted_at":"2024-12-28T04:06:44Z","title":"Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions"},"reference_resolution":{"displayed":20,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":17},"total_outbound_references":20},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2412.20007."}