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
Journal of Nutrition Education and Behavior
Topic
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.

4,708 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.
4,708 works in the cohort · of 4,299,418page 51 of 95

Labels cover 8 of 4,708 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 4,708 of 4,708 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.

fundvenueno affno abstractunlabeled
P167 Feasibility of ASA-24 in Community-Based Settings
Hannah Wilson, Bradley Averill, Georgeanne Cook, Jackie Dallas, Christa Campbell, Jessica A. M. Moore +10 more
2020· article· en· Journal of Nutrition Education and Behavior· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
How DO You Do It? Let Your Readers Know
Lauren Haldeman
2024· editorial· en· Journal of Nutrition Education and Behavior· Social Sciences
machine prediction:candidate · metaresearchconsensus · none
1
citations
venueno affno abstractunlabeled
Nutrition Notes to Go
Christen Cupples Cooper
2019· article· en· Journal of Nutrition Education and Behavior· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
venueno affno abstractunlabeled
Refrigerator Art to Promote 5 A Day
Patti S. Landers
2003· article· en· Journal of Nutrition Education and Behavior· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
2050: The Year of Our Carbon-Neutral Food System
Jasia Steinmetz
2021· editorial· en· Journal of Nutrition Education and Behavior· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
Reply to Miller et al, Letter to the Editor, SNEB
Hugh M. Joseph, Pamela Koch, Mim Seidel, Jasia Steinmetz, Jennifer L. Wilkins
2020· letter· en· Journal of Nutrition Education and Behavior· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
P45
Leslie Cunningham‐Sabo, Barbara Lohse, Lynn Walters, Jane E. Stacey, Candice Hewitt-Redl
2007· article· en· Journal of Nutrition Education and Behavior· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
venueno affno abstractunlabeled
Developing Food Products and Enthusiastic Learners
M.W. Duffrin, Diane N. Cuson, Sharon Phillips, Annette S. Graham
2005· article· en· Journal of Nutrition Education and Behavior· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About