Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T05:38:16.272238Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2508.01460.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T05:38:16.272238Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
38 of 38 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 88d012c6-1582-4f99-bb97-ad34b2485cd5 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 1
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Observation cbb0fe9e-931f-41bb-b683-27a30eca870f · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 2
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Observation dc9e205b-364a-491b-81d8-390adcfe2415 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Valindria et al., Reverse classification accuracy: predicting segmentation performance in the absence of ground truth, IEEE transactions on medical imaging 36 (8) (2017) 1597--1606
Reference 3
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Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 4
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Reference 5
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Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 6
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Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 7
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Reference 8
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Observation 7d817a37-8366-42e9-a071-618ade0c7f9f · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 9
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Observation bcb78b1e-04c5-4d56-95bb-b4eba4364377 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Robinson et al., Subject-level prediction of segmentation failure using real-time convolutional neural nets (2018)
Reference 10
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Observation 3663e7a6-afdd-4047-8219-66f0db995555 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 11
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Observation 56c5ce51-6906-4386-a72a-9f41c8072d4e · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Robust Image Segmentation Quality Assessment
Reference 12
Source-reported events for the cited work
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Observation 5dcd7353-40c7-48f3-a9b3-c00502c1f0d8 · outbound
Reference 13
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Observation 1a45cb50-5bca-41de-a42b-60b7a37e7c70 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Leveraging Uncertainty Estimates for Predicting Segmentation Quality
Reference 14
Source-reported events for the cited work
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Observation 554fb733-5e9f-4c85-ba8f-f2d446e77151 · outbound
Reference 15
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Reference 16
Source-reported events for the cited work
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Observation f45acb14-75a3-424a-8c52-aab6423f0d99 · outbound
Reference 17
Source-reported events for the cited work
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Observation dc1a1d7f-72e7-4540-8715-d61aa33ddb69 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 18
Source-reported events for the cited work
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Observation 49349878-63e7-4790-a09a-60c0db0ed043 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 19
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Observation 172b582c-fb39-4c8a-96af-6f3a42597180 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 20
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Observation 73192ddc-1496-4ec3-b92e-1328c333c993 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 21
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Reference 22
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Reference 23
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Observation 8a34a2ae-e507-4413-86cd-e6543b26b92f · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 24
Source-reported events for the cited work
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Observation 975cd7ef-ee24-4646-894c-4a744e1b5d21 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Lakshminarayanan, A
Reference 25
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Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation
Reference 26
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Observation 866b71d3-61f0-4140-bd05-14b788150999 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 27
Source-reported events for the cited work
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Observation e79f60e7-db62-4c11-85dd-b53f71907854 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 28
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Observation 7b730a03-ed1f-482b-8bd2-bcc22faf8ab9 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 29
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Reference 30
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Observation 71aa0310-6ac4-4c7e-8f7f-e726ab389ecf · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)
Reference 31
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Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Unresolved cited work
Reference 32
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Observation 1bb65b8a-5351-4068-856e-2c1361ef2066 · outbound
Reference 33
Source-reported events for the cited work
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Observation 758e89d0-813c-4d3f-81b6-628690bd3e97 · outbound
Reference 34
Source-reported events for the cited work
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Observation c5f80fce-cec9-4e49-8328-3636b4bb67ef · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation The Liver Tumor Segmentation Benchmark (LiTS)
Reference 35
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Observation eb9c5901-09ca-45d8-ac85-beecd793c470 · outbound
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation Learning Confidence for Out-of-Distribution Detection in Neural Networks
Reference 36
Source-reported events for the cited work
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Reference 37
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Observation 4e5b9a95-bb11-4f97-b8e5-a6a9a2f5c80f · outbound
Reference 38
Source-reported events for the cited work
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No inbound Pith citation observations are available.