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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Explainable Artificial Intelligence (XAI)
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

675 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
675 works in the cohort · of 4,299,418page 1 of 14

Labels cover 1 of 675 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 675 of 675 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affunlabeled
A review of Explainable Artificial Intelligence in healthcare
Zahra Sadeghi, Roohallah Alizadehsani, Mehmet Akif Çifçi, Samina Kausar, Rizwan Rehman, Priyakshi Mahanta +10 more
2024· review· en· Computers & Electrical Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
438
citations
affno abstractunlabeled
Explainable AI: The New 42?
Randy Goebel, Ajay Chander, Katharina Holzinger, Freddy Lécué, Zeynep Akata, Simone Stumpf +2 more
2018· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
252
citations
affunlabeled
Human-Centered Explainable AI (HCXAI): Beyond Opening the Black-Box of AI
Upol Ehsan, Philipp Wintersberger, Q. Vera Liao, Elizabeth Anne Watkins, Carina Manger, Hal Daumé +2 more
2022· article· en· CHI Conference on Human Factors in Computing Systems Extended Abstracts· Computer Science
machine prediction:candidate · noneconsensus · none
105
citations
affunlabeled
Impossibility theorems for feature attribution
Blair Bilodeau, Natasha Jaques, Pang Wei Koh, Been Kim
2024· article· en· Proceedings of the National Academy of Sciences· Computer Science
machine prediction:candidate · noneconsensus · none
88
citations
affunlabeled
Sensitivity analysis: A discipline coming of age
Andrea Saltelli, Anthony J. Jakeman, Saman Razavi, Qiongli Wu
2021· article· en· Environmental Modelling & Software· Computer Science
machine prediction:candidate · metaresearchconsensus · none
84
citations
affunlabeled
Explainable Artificial Intelligence (XAI)
Michael Ridley
2022· article· en· Information Technology and Libraries· Computer Science
machine prediction:candidate · noneconsensus · none
82
citations
fundno affunlabeled
What is Interpretability?
Adrian Erasmus, T. D. P. Brunet, Eyal Fisher
2020· article· en· Philosophy & Technology· Computer Science
machine prediction:candidate · noneconsensus · none
74
citations

How this was built: Screen · Findings · About