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endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.19372.

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pith.paper-citation-record.v1
2607.19372 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:01:20.868235Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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  • verified fuzzy0
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Outbound references

Observation 647b8b56-c721-4826-b4f7-d56f13619dcf · outbound

This paper cites Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy

Reference 1

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Observation 03b88413-7347-4109-85ae-898e3e202dd6 · outbound

This paper cites Diagnostic accuracy of artificial intelligence in endoscopy: Umbrella review.JMIR Medical Informatics, 12:e56361, 2024.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Diagnostic accuracy of artificial intelligence in endoscopy: Umbrella review.JMIR Medical Informatics, 12:e56361, 2024

Reference 2

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Observation fc7ef446-5eea-4c19-8ed7-5e4bf6f89cff · outbound

This paper cites A prospective multicenter randomized controlled trial on artificial intelligence assisted colonoscopy for enhanced polyp detection.Scientific Reports, 14(1):25453, 2024.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers A prospective multicenter randomized controlled trial on artificial intelligence assisted colonoscopy for enhanced polyp detection.Scientific Reports, 14(1):25453, 2024

Reference 3

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Observation 4a2950c7-651b-47a2-a8a7-428a3a810b6c · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient- based localization.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Grad-cam: Visual explanations from deep networks via gradient- based localization

Reference 4

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Observation e72739d2-34b5-4891-8582-9ea006b8153a · outbound

This paper cites Grad-cam++: Generalized gradient-based visual explanations for deep convolutional net- works.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Grad-cam++: Generalized gradient-based visual explanations for deep convolutional net- works

Reference 5

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Observation 8f373274-ecf9-4539-8c65-6474488d1a47 · outbound

This paper cites Axiom- based Grad-CAM: Towards accurate visualization and explanation of CNNs.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Axiom- based Grad-CAM: Towards accurate visualization and explanation of CNNs

Reference 6

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Observation 0815adc6-f421-4acc-bd40-d5c0b55c8353 · outbound

This paper cites Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks, 2021.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks, 2021

Reference 7

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Observation 6fb0cb5b-0b63-4b0f-a016-a43df954e9f6 · outbound

This paper cites Sanity checks for saliency maps.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Sanity checks for saliency maps

Reference 8

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Observation abfd5e8a-71b6-44dc-9e60-53e9524fff84 · outbound

This paper cites Evaluating the visualization of what a deep neural network has learned.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Evaluating the visualization of what a deep neural network has learned

Reference 9

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Observation 5fd55965-a56e-4805-a88b-f170190baeee · outbound

This paper cites A benchmark for interpretability methods in deep neural networks.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers A benchmark for interpretability methods in deep neural networks

Reference 10

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Observation 9e1f7eae-7e42-4a56-8561-e3b572e085c5 · outbound

This paper cites A consistent and efficient evaluation strategy for attribution methods.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers A consistent and efficient evaluation strategy for attribution methods

Reference 11

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Observation f0ea3443-460b-4bb1-b3a4-f3e86b52c0d0 · outbound

This paper cites Uncertainty and inter- pretability in convolutional neural networks for semantic segmentation of colorectal polyps.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Uncertainty and inter- pretability in convolutional neural networks for semantic segmentation of colorectal polyps

Reference 12

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Observation ad1df702-23ec-4c6e-8f10-c35db6c4da39 · outbound

This paper cites Assessing the trust- worthiness of saliency maps for localizing abnormalities in medical imaging.Radiology: Artificial Intelligence, 3(6):e200267, 2021.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Assessing the trust- worthiness of saliency maps for localizing abnormalities in medical imaging.Radiology: Artificial Intelligence, 3(6):e200267, 2021

Reference 13

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Observation a04ffb52-be87-4f05-8d31-507960f4081e · outbound

This paper cites Hyperkvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy.Scientific Data, 7(1):283, 2020.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Hyperkvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy.Scientific Data, 7(1):283, 2020

Reference 14

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Observation 963c5c2d-3250-40d4-8793-eb863527d5db · outbound

This paper cites Toward embedded detection of polyps in wce images for early diagnosis of colorectal cancer.In- ternational Journal of Computer Assisted Radiology and Surgery, 9(2):283–293, 2014.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Toward embedded detection of polyps in wce images for early diagnosis of colorectal cancer.In- ternational Journal of Computer Assisted Radiology and Surgery, 9(2):283–293, 2014

Reference 15

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Observation 9d616f68-c8b4-40ba-9297-5e7808b0ec57 · outbound

This paper cites Salem, Dominique Lamarque, Christian Daul, Michael A.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Salem, Dominique Lamarque, Christian Daul, Michael A

Reference 16

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Observation 980377f7-f99d-4f30-852d-299856ed4ce4 · outbound

This paper cites PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy

Reference 17

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Observation e28a5a6b-fc29-4477-a6ed-fcb88764fe5a · outbound

This paper cites Eigen-cam: Class activation map using principal components.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Eigen-cam: Class activation map using principal components

Reference 18

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Observation ec3ba07c-d336-4ba7-81a8-b992976be5d6 · outbound

This paper cites an unresolved cited work.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Unresolved cited work

Reference 19

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Observation a111d46e-e558-4fe8-9346-8b923ce4c5ae · outbound

This paper cites RISE:Randomizedinputsamplingforexplanation of black-box models.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers RISE:Randomizedinputsamplingforexplanation of black-box models

Reference 20

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Observation 012192fd-c71c-44fd-8768-e509a4fe8c1f · outbound

This paper cites Storås, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Wojciech Samek, Pål Halvorsen, Thomas de Lange, Yuichi Mori, Alexander Hann, Tyler M.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Storås, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Wojciech Samek, Pål Halvorsen, Thomas de Lange, Yuichi Mori, Alexander Hann, Tyler M

Reference 21

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Observation dc048e67-2bed-4984-9334-37d4569d4baa · outbound

This paper cites Lago, Ghada Zamzmi, Brandon Eich, and Jana G.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Lago, Ghada Zamzmi, Brandon Eich, and Jana G

Reference 22

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Observation dd19972a-2c98-4387-8951-e24443326c1e · outbound

This paper cites artificial intelligence in endoscopy.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers artificial intelligence in endoscopy

Reference 23

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Observation 9f01de89-3c74-4fd7-a617-1c83d8bbcf23 · outbound

This paper cites LDPolypVideo benchmark: A large-scale colonoscopy video dataset of diverse polyps.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers LDPolypVideo benchmark: A large-scale colonoscopy video dataset of diverse polyps

Reference 24

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Observation 301d8387-0d17-42cb-b1df-8e8517b22e4c · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 25

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Observation cb440c63-806f-4978-b18a-72128defee56 · outbound

This paper cites Deep residual learning for image recognition.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Deep residual learning for image recognition

Reference 26

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Observation 0888fccc-4ec9-4ed8-a46a-8ed5743a6f1f · outbound

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endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers A convnet for the 2020s

Reference 27

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Observation 9e5e859a-8952-44c8-967b-d15ad690a8dd · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Pytorch: An imperative style, high-performance deep learning library

Reference 28

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Observation d2b2bd06-1609-4dbc-b650-e55fe346ca59 · outbound

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endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Torchvision the machine-vision package of torch

Reference 29

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Observation 9b6a2cd9-d22b-4850-87a4-d20310f513b5 · outbound

This paper cites Albumentations: Fast and flexible image augmentations.

endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Albumentations: Fast and flexible image augmentations

Reference 30

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endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Mixed precision training

Reference 31

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Observation d4a3858c-feca-4bb3-a6e5-db1dda089edd · outbound

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endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Weinberger

Reference 32

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Observation 6da744dd-10e0-4d6c-98fa-42c41e6bb963 · outbound

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endoExplain: A reproducible protocol for auditing score-localisation discordance in colonoscopy image classifiers Unresolved cited work

Reference 2010

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