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
Occupational Health and Performance
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.

777 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.
777 works in the cohort · of 4,299,418page 4 of 16

Labels cover 4 of 777 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 777 of 777 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 affno abstractunlabeled
Development and Validation of the Military Eating Behavior Survey
Renee E. Cole, Julianna M. Jayne, Kristie O’Connor, Susan M. McGraw, Robbie A. Beyl, Adam J. DiChiara +1 more
2021· article· en· Journal of Nutrition Education and Behavior· Health Professions
machine prediction:candidate · noneconsensus · none
26
citations
affunlabeled
Factors in Adoption of a Fire Department Wellness Program
Hannah Kuehl, Linda Mabry, Diane L. Elliot, Kerry S. Kuehl, Kim C Favorite
2013· article· en· Journal of Occupational and Environmental Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
25
citations
affaboutunlabeled
Quebec Serve and Protect Low Back Pain Study
Nabiha Benyamina Douma, Charles J. Coté, Anaïs Lacasse
2017· article· en· Spine· Health Professions
machine prediction:candidate · noneconsensus · none
23
citations
afffundaboutunlabeled
Cancer risk among firefighters and police in the Ontario workforce
Jeavana Sritharan, Tracy L Kirkham, Jill MacLeod, Niki Marjerrison, Ashley Lau, Mamadou Dakouo +4 more
2022· article· en· Occupational and Environmental Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
23
citations
aboutno affunlabeled
Firefighters and COVID-19: An Occupational Health Perspective
Elliot L. Graham, Saeed U. Khaja, Alberto J. Caban‐Martinez, Denise L. Smith
2021· article· en· Journal of Occupational and Environmental Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
22
citations
afffundaboutunlabeled
A description of musculoskeletal injuries in a Canadian police service
Liana Lentz, Donald C. Voaklander, Douglas P. Gross, Christine Guptill, Ambikaipakan Senthilselvan
2019· article· en· International Journal of Occupational Medicine and Environmental Health· Health Professions
machine prediction:candidate · noneconsensus · none
21
citations
aboutno affunlabeled
Lung Cancer Among Firefighters
Carolina Bigert, Per Gustavsson, Kurt Straíf, Dirk Taeger, Beate Pesch, Benjamin Kendzia +39 more
2016· article· en· Journal of Occupational and Environmental Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
21
citations

How this was built: Screen · Findings · About