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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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Substance Abuse Treatment and Outcomes
Retraction
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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.

3,732 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.
3,732 works in the cohort · of 4,299,418page 15 of 75

Labels cover 16 of 3,732 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 3,732 of 3,732 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.

affaboutno abstractunlabeled
Heavy drinking on Canadian campuses.
Louis Gliksman, Edward M. Adlaf, Andrée Demers, Brenda Newton-Taylor
2003· article· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Judging intoxication
Steve Rubenzer
2010· review· en· Behavioral Sciences & the Law· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
afffundno abstractunlabeled
Self-coded indirect memory associations and
Marvin D. Krank, Tara Schoenfeld, Aarin P. Frigon
2010· article· en· Behavior Research Methods· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Lifecourse SEP and tobacco and cannabis use
Lucy Bowes, A. Chollet, Éric Fombonne, Cédric Galéra, Maria Melchior
2012· article· en· European Journal of Public Health· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
The cultural aspect
Jürgen Rehm, Robin Room
2017· article· en· Nordic Studies on Alcohol and Drugs· Medicine
machine prediction:candidate · noneconsensus · none
31
citations
fundno affunlabeled
The Alcohol Environment Protocol: A new tool for alcohol policy
Sally Casswell, Neo K. Morojele, Petal Petersen Williams, Surasak Chaiyasong, Ross Gordon, Gaile Gray‐Phillip +6 more
2018· article· en· Drug and Alcohol Review· Medicine
machine prediction:candidate · noneconsensus · none
31
citations
afffundvenueunlabeled
Predictors of Alcohol and Drug Dependence
Marie‐Josée Fleury, Guy Grenier, Jean-Marie Bamvita, Michel Perreault, Jean Caron
2014· article· en· The Canadian Journal of Psychiatry· Medicine
machine prediction:candidate · noneconsensus · none
31
citations
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How this was built: Screen · Findings · About