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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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Healthcare Systems and Practices
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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.

3,912 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.
3,912 works in the cohort · of 4,299,418page 41 of 79

Labels cover 15 of 3,912 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 3,912 of 3,912 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.

affaboutunlabeled
Un éclairage du droit québécois
Tanaquil Burke
2007· article· fr· Retraite et société· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Le pouvoir de la langue
Melanie Elhafid
2021· article· fr· University of Ottawa Journal of Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Exploration des différences dans les comportements liés à la consommation de substances chez les jeunes faisant partie de minorités de genre et les jeunes ne faisant pas partie de minorités de genre : analyse transversale de l’étude COMPASS
Thepikaa Varatharajan, Karen A. Patte, Margaret de Groh, Ying Jiang, Scott T. Leatherdale
2024· article· fr· Promotion de la santé et prévention des maladies chroniques au Canada· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Communications numériques en santé
Nicolas Peirot
2021· article· fr· Communiquer Revue de communication sociale et publique· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Question de défense
Bruno Le Maire
2016· article· fr· Revue Défense Nationale· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
L’AUC – étendre sa portée
Joseph L. Chin
2012· article· fr· Canadian Urological Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Errata
2005· article· fr· Relations industrielles· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affvenueaboutunlabeled
L’AUC comme promoteur de la santé
Jerzy B. Gajewski
2013· article· fr· Canadian Urological Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Heros de la promotion de la sante
James Douketis
2019· article· fr· Canadian Journal of General Internal Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
L'accès aux sources mis à mal
Serge Marti
2006· article· fr· Revue Projet· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Des services pensés pour tous les publics
Hélène Roussel, Danielle Chagnon, Sylvie Fournier
2015· article· fr· Documentation et bibliothèques· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About