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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.

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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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Artificial Intelligence in Healthcare and Education
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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.

3,498 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.
3,498 works in the cohort · of 4,299,418page 2 of 70

Labels cover 44 of 3,498 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 3,498 of 3,498 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
ChatGPT in healthcare: A taxonomy and systematic review
Jianning Li, Amin Dada, Behrus Puladi, Jens Kleesiek, Jan Egger
2024· review· en· Computer Methods and Programs in Biomedicine· Medicine
distilled prediction:candidate · metaepi_narrowconsensus · none
332
citations
affunlabeled
Surgical data science – from concepts toward clinical translation
Lena Maier‐Hein, Matthias Eisenmann, Duygu Sarıkaya, Keno März, Toby Collins, Anand Malpani +45 more
2022· review· en· univOAK (4 institutions : Université de Strasbourg, Université de Haute Alsace, INSA Strasbourg, Bibliothèque Nationale et Universitaire de Strasbourg)· Medicine
distilled prediction:candidate · metaepi_narrow+sts+research_integrity+insufficient_payloadconsensus · metaepi_narrow+sts+research_integrity
332
citations
affno abstractunlabeled
Pandemic publishing poses a new COVID-19 challenge
Adam Palayew, Ole Nørgaard, Kelly Safreed‐Harmon, Tue Helms Andersen, Lauge Neimann Rasmussen, Jeffrey V. Lazarus
2020· article· en· Nature Human Behaviour· Medicine
distilled prediction:candidate · noneconsensus · none
272
citations
affunlabeled
Beware explanations from AI in health care
Boris Babic, Sara Gerke, Theodoros Evgeniou, I. Glenn Cohen
2021· article· en· Science· Medicine
distilled prediction:candidate · noneconsensus · none
231
citations
affunlabeled
The medical algorithmic audit
Xiaoxuan Liu, Ben Glocker, Melissa D. McCradden, Marzyeh Ghassemi, Alastair K. Denniston, Lauren Oakden‐Rayner
2022· review· en· The Lancet Digital Health· Medicine
distilled prediction:candidate · noneconsensus · none
223
citations
affno abstractunlabeled
The impact of machine learning on patient care: A systematic review
David Ben‐Israel, W. Bradley Jacobs, Steve Casha, Stefan Lang, Won Hyung A. Ryu, Madeleine de Lotbinière-Bassett +1 more
2019· review· en· Artificial Intelligence in Medicine· Medicine
distilled prediction:candidate · metaepi_narrowconsensus · none
209
citations
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How this was built: Screen · Findings · About