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Paper Citation Record · LEDGER

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification

As of 21 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2506.18414.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.18414 v3

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:20:06.280520Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

10 of 10 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 57933fff-3752-468f-9a69-f0fead639e19 · outbound

This paper cites Trends in malignant melanoma mortality in 31 countries from 1985 to 2015.British Journal of Dermatology, 183(6):1056–1064, 2020.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Trends in malignant melanoma mortality in 31 countries from 1985 to 2015.British Journal of Dermatology, 183(6):1056–1064, 2020

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:07.164698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T23:20:05.344865Z digest=sha256:27aed07698a358e4aaaf14127af6a6a4425aa06c28cac66d3fb05a7f1491dfa9

Observation ab1328bb-f77d-42b3-bbc5-835e946041f0 · outbound

This paper cites Classification of melanoma and nevus in digital images for diagnosis of skin cancer.IEEE Access, 7:90132–90144, 2019.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Classification of melanoma and nevus in digital images for diagnosis of skin cancer.IEEE Access, 7:90132–90144, 2019

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:06.903053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T23:20:05.402479Z digest=sha256:e7bc68efe95da9462e3081c91c791a1c0cd0721ad8b365481199b937ff42c617

Observation 79e920cc-3793-41d4-a632-d7ee8930d8df · outbound

This paper cites Auto-encoding variational bayes, 2013.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Auto-encoding variational bayes, 2013

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:05.517590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:05.517590Z digest=sha256:8a2e935c9dd86fe91c79c6a7185604b59ada5acc5de4fdaf954c70b0d3477e40

Observation 88bec377-269e-452e-996f-8ecadd098eb7 · outbound

This paper cites Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:06.766382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T23:20:05.602953Z digest=sha256:ddc7103acbd4017d6d612340c0c068b0ec0129473634c7be8f58e29a845e979b

Observation 664cc45f-5895-4aa9-9a0d-5a2a923bd444 · outbound

This paper cites Anomaly Detection for Skin Disease Images Using Variational Autoencoder.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Anomaly Detection for Skin Disease Images Using Variational Autoencoder

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:05.733125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:05.733125Z digest=sha256:4772b0d06cfb1d4b76cc40dfdf666d73edc5bdd063f294fd47344f3e57f9ad6a

Observation 3a552ff5-f0f5-4f0b-8a2a-92d798fb6769 · outbound

This paper cites Sensitivity analysis of latent variables in variational autoencoders for dermoscopic image analysis.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Sensitivity analysis of latent variables in variational autoencoders for dermoscopic image analysis

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:06.569229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T23:20:05.824180Z digest=sha256:598128dbff960ca78e25f024bf0dbecef77a254c5931b9bb10b2d018496ab062

Observation 3375c1eb-6b4f-4552-a9c3-290bacbf75d5 · outbound

This paper cites Exploring Variational Autoencoders for Medical Image Generation: A Comprehensive Study.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Exploring Variational Autoencoders for Medical Image Generation: A Comprehensive Study

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:05.916050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:05.916050Z digest=sha256:05a564a86dacbda2b35957615cbe9ad77ebd1ed314cc7b4a4cf2c09a7244d738

Observation 51ece513-aab8-4bc7-9b6b-fe9348170075 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, 5(1):1–9, 2018.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, 5(1):1–9, 2018

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:06.043551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:06.043551Z digest=sha256:4fa9aa64d5a5a5edee33a642c5524e8a1a318b8493a5a53f04dd218161d20982

Observation cd8ee904-86e6-4255-9fa7-3a57af63a2f2 · outbound

This paper cites an unresolved cited work.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:06.181393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:06.181393Z digest=sha256:740ffcc982a79b6252d20b9a5ffcf75e1c917324762a02f645e8cb208a7d326c

Observation 99840f5c-aaf0-4c1a-9447-ce22e09b1c8e · outbound

This paper cites BCN20000: Dermoscopic Lesions in the Wild.

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification BCN20000: Dermoscopic Lesions in the Wild

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:06.280520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:06.280520Z digest=sha256:0e98ecb41baee0dc034e354081824f326c9f5d2bc09eb8b4723ee68bbd42a4d1

Pith citing papers

No inbound Pith citation observations are available.