Paper Citation Record · LEDGER

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models

As of 20 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2509.11184.

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

pith.paper-citation-record.v1
2509.11184 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:01:07.271633Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

22 of 22 outbound references displayed

verified exact0
verified fuzzy0
unresolved21
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab5464e4-6446-475a-8d02-950dbdfb28da · outbound

This paper cites Appl Sci14(2024).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Appl Sci14(2024)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.122956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ab0facb-f71c-4d8a-8422-c23a0efc813d · outbound

This paper cites Dermatol Nurs21, 170–177 (2009).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Dermatol Nurs21, 170–177 (2009)

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.130564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7a7004f-2c63-43b4-a156-7d39b9bd764e · outbound

This paper cites Int J Cosmet Sci13(4), 191–208 (1991).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Int J Cosmet Sci13(4), 191–208 (1991)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.137878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4979539-d150-4506-8695-f8f7369e6cf6 · outbound

This paper cites JAMA Dermatol157(11), 1362–1369 (2021).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models JAMA Dermatol157(11), 1362–1369 (2021)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.143901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 187bce5c-d12c-49c1-b4c2-24b33e206a82 · outbound

This paper cites Sci Adv8(32), eabq6147 (2022).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Sci Adv8(32), eabq6147 (2022)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.154198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 195975af-bb82-4511-8575-913e6b874939 · outbound

This paper cites Ko, S.M.S., Blau, H.M., Thrun, S.: Dermatologist-level classification of skin cancer with deep neural networks.

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Ko, S.M.S., Blau, H.M., Thrun, S.: Dermatologist-level classification of skin cancer with deep neural networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.162861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33ef9723-8597-4e4d-8af5-4acaedf4fc33 · outbound

This paper cites Arch Dermatol124(6), 869–871 (1988).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Arch Dermatol124(6), 869–871 (1988)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.169865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a1c6da-6288-4669-81ea-367f1512f7dc · outbound

This paper cites In: Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.175634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b7b0ab0-6bf1-4741-a54a-b12a08509c06 · outbound

This paper cites In: Proceedings of International Conference on Machine Learning (ICML) (2017).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of International Conference on Machine Learning (ICML) (2017)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.184762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3dd8af8-fdd0-4365-a2c8-cf38f48a0b8b · outbound

This paper cites In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017) 10 P.

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017) 10 P

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.189971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6126a927-827c-4c0a-9770-546a8ceb545b · outbound

This paper cites Knowl Inf Syst33, 1–33 (2012).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Knowl Inf Syst33, 1–33 (2012)

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.196717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96bb9dff-2c0c-4d63-a4e7-6820c26669ef · outbound

This paper cites an unresolved cited work.

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Unresolved cited work

Reference 12

Resolution: malformed identifier; doi_truncated, observed 2026-08-04T17:04:04.304637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dd409a4c-578b-47d0-9366-029af092068c · outbound

This paper cites In: Proceedings of Machine Learning for Healthcare (MLHC) (2023).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of Machine Learning for Healthcare (MLHC) (2023)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.209023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cf37db2-4ccb-45db-b983-72bb4570c494 · outbound

This paper cites Br J Dermatol185(1), 198–199 (2021).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Br J Dermatol185(1), 198–199 (2021)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.216037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b73a840a-103e-48ca-9a10-b763a81a42f3 · outbound

This paper cites In: Proceedings of European Conference on Computer Vision (ECCV) (2022).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of European Conference on Computer Vision (ECCV) (2022)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.222476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dc6c4ee-0514-4099-be27-8467a112f47e · outbound

This paper cites In: Proceedings of Medical Image Computing and Computer Assisted Interventions (MICCAI).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of Medical Image Computing and Computer Assisted Interventions (MICCAI)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.229552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cb43a44-12ad-447a-ae44-ec7c7b6fbb38 · outbound

This paper cites Beyond Skin Tone: A Multidimensional Measure of Apparent Skin Color.

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Beyond Skin Tone: A Multidimensional Measure of Apparent Skin Color

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.237807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 591889e4-e8cd-4685-945b-0e130a619ca8 · outbound

This paper cites In: Proceedings of International Conference on Machine Learning (ICML) (2020).

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.243675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 982ead21-78e1-4b1d-9a15-ea2926bff854 · outbound

This paper cites In: Proceedings of the 36th International Conference on Machine Learning (2019),https://proceedings.mlr.press/v97/ustun19a.html.

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of the 36th International Conference on Machine Learning (2019),https://proceedings.mlr.press/v97/ustun19a.html

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.249795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c67052fd-abb1-4b51-988d-89fe7044186b · outbound

This paper cites Cutis105(2), 77–80 (2020).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models Cutis105(2), 77–80 (2020)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.260095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1129946-8c39-434a-971c-b23249d611e2 · outbound

This paper cites npj Digit Med7(191) (2024).

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models npj Digit Med7(191) (2024)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.265569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7d3ec3a-7a94-4665-a00a-780843f91218 · outbound

This paper cites In: Proceedings of Conference on Health, Inference, and Learning.

The Impact of Skin Tone Label Granularity on the Performance and Fairness of AI Based Dermatology Image Classification Models In: Proceedings of Conference on Health, Inference, and Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:07.271633Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.