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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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Advances in Health Sciences 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.

539 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.
539 works in the cohort · of 4,299,418page 7 of 11

Labels cover 4 of 539 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 539 of 539 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.

affno abstractunlabeled
Where we’ve come from, where we might go
Geoff Norman
2020· article· en· Advances in Health Sciences Education· Medicine
machine prediction:candidate · noneconsensus · none
12
citations
affno abstractunlabeled
It’s the destination: diagnostic accuracy and reasoning
Sandra Monteiro, Jonathan Sherbino, Henk G. Schmidt, Sílvia Mamede, Jonathan S. Ilgen, Geoff Norman
2019· article· en· Advances in Health Sciences Education· Medicine
machine prediction:candidate · noneconsensus · none
12
citations
affno abstractunlabeled
May: a month of myths
Geoff Norman
2018· editorial· en· Advances in Health Sciences Education· Medicine
machine prediction:candidate · noneconsensus · none
11
citations
affno abstractunlabeled
Effectiveness, efficiency, and e-learning
Geoff Norman
2008· letter· en· Advances in Health Sciences Education· Social Sciences
machine prediction:candidate · noneconsensus · none
11
citations
affno abstractunlabeled
Looking back, looking forward
Geoff Norman, Rachel Ellaway
2020· article· en· Advances in Health Sciences Education· Medicine
machine prediction:candidate · noneconsensus · none
9
citations
affno abstractunlabeled
Peer review is not a lottery: AHSE’s Fast Track
Rachel Ellaway, Martin G. Tolsgaard, Geoff Norman
2020· article· en· Advances in Health Sciences Education· Medicine
machine prediction:candidate · metaresearchconsensus · none
9
citations
affno abstractunlabeled
Context, curriculum and competence
Geoff Norman
2014· editorial· en· Advances in Health Sciences Education· Medicine
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Good news, bad news
Geoff Norman
2018· editorial· en· Advances in Health Sciences Education· Social Sciences
machine prediction:candidate · research_integrityconsensus · none
9
citations

How this was built: Screen · Findings · About