MétaCan
Menu
Cohort builder

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.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Topic
Posttraumatic Stress Disorder Research
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

1,955 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,955 works in the cohort · of 4,299,418page 15 of 40

Labels cover 3 of 1,955 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 1,955 of 1,955 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.

afffundvenueaboutunlabeled
Course and Predictors of Major Depressive Disorder in the Canadian Armed Forces Members and Veterans Mental Health Follow-up Survey: Cours et Prédicteurs du Trouble de Dépression Majeure Dans l’Enquête de Suivi Sur la Santé Mentale Auprès Des Membres des Forces Armées Canadiennes et des ex-Militaires
Murray W. Enns, Natalie Mota, Tracie O. Afifi, Shay‐Lee Bolton, Julie Richardson, Scott B. Patten +1 more
2021· article· en· The Canadian Journal of Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
21
citations
affunlabeled
Understanding PTSD: Implications for Court
Gerald Young, Rachel Yehuda
2006· book-chapter· en· Kluwer Academic Publishers eBooks· Psychology
machine prediction:candidate · noneconsensus · none
21
citations
afffundvenueaboutunlabeled
Rationale and Methodology of the 2018 Canadian Armed Forces Members and Veterans Mental Health Follow-up Survey (CAFVMHS): A 16-year Follow-up Survey: Raison D’être Et Méthodologie De L’enquête De Suivi Sur La Santé Mentale Des Membres Des Forces Armées Canadiennes Et Des Anciens Combattants, 2018 (ESSMFACM)
Tracie O. Afifi, Shay‐Lee Bolton, Natalie Mota, Ruth Ann Marrie, Murray B. Stein, Murray W. Enns +9 more
2020· article· en· The Canadian Journal of Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
21
citations
afffundvenueaboutunlabeled
Association of Child Maltreatment and Deployment-related Traumatic Experiences with Mental Disorders in Active Duty Service Members and Veterans of the Canadian Armed Forces: Association de la Maltraitance des Enfants et des Expériences Traumatisantes Liées au Déploiement Avec les Troubles Mentaux Chez les Membres du Service Actif et Les Anciens Combattants des Forces Armées Canadiennes
Tracie O. Afifi, Jitender Sareen, Tamara Taillieu, Ashley Stewart-Tufescu, Natalie Mota, Shay‐Lee Bolton +4 more
2021· article· en· The Canadian Journal of Psychiatry· Psychology
machine prediction:candidate · noneconsensus · none
20
citations

How this was built: Screen · Findings · About