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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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Statistics Education and Methodologies
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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.

affaffiliation
fundfunder
venuejournal
aboutaboutness

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

595 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
595 works in the cohort · of 4,299,418page 4 of 12

Labels cover 5 of 595 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 595 of 595 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.

venueno affunlabeled
Model-based Informal Inference
Theodosia Prodromou
2017· article· en· International Journal of Statistics and Probability· Mathematics
machine prediction:candidate · noneconsensus · none
5
citations
fundno affunlabeled
The double-edged sword of conjecturing
Michal Dvir, Dani Ben‐Zvi
2021· article· en· Mathematical Thinking and Learning· Mathematics
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Comparing the Relative Probabilities of Events
Egan J. Chernoff, Ilona Vashchyshyn, Heidi Neufeld
2018· book-chapter· en· ICME-13 monographs· Mathematics
machine prediction:candidate · noneconsensus · none
4
citations
affvenueaboutno abstractunlabeled
L’analyse de tâches probabilistes proposées dans des cahiers d’apprentissage destinés à l’enseignement-apprentissage des mathématiques au primaire au Québec : exemplification de tâches inscrites dans l’approche fréquentielle
Vincent Martin, Sabrina Héroux, Marianne Homier, Mathieu Thibault
2021· article· fr· Canadian Journal of Science Mathematics and Technology Education· Mathematics
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractgemma · metaresearchgpt · bibliometricsmodels split
Statistical tests for ‘related records’ search results
Charles H. Smith, Patrick Georges, Ngoc Cuong Nguyen
2015· article· en· Scientometrics· Mathematics
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
4
citations
affunlabeled
Naive Analysis of Variance
W. John Braun
2012· article· en· Journal of Statistics Education· Mathematics
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Comment
Alison L. Gibbs, Nancy Reid
2009· article· en· The American Statistician· Mathematics
machine prediction:candidate · insufficient_payloadconsensus · none
4
citations

How this was built: Screen · Findings · About