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
Behavioural Processes
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.

317 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.
317 works in the cohort · of 4,299,418page 1 of 7

Labels cover 0 of 317 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 317 of 317 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.

affno abstractunlabeled
What is emotion?
Michel Cabanac
2002· article· en· Behavioural Processes· Psychology
machine prediction:candidate · noneconsensus · none
634
citations
afffundno abstractunlabeled
Object familiarization and novel-object preference in rats
Stéphane Gaskin, Marilyn Tardif, Emily Cole, Pavel Piterkin, Lima Kayello, Dave G. Mumby
2009· article· en· Behavioural Processes· Neuroscience
machine prediction:candidate · noneconsensus · none
132
citations
affno abstractunlabeled
Beginnings of a synthetic approach to desert ant navigation
Ken Cheng, Patrick Schultheiss, Sebastian Schwarz, Antoine Wystrach, Rüdiger Wehner
2013· review· en· Behavioural Processes· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
80
citations
afffundunlabeled
Is play a behavior system, and, if so, what kind?
Sergio M. Pellis, Vivien C. Pellis, Amanda Pelletier, Jean‐Baptiste Leca
2019· review· en· Behavioural Processes· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
72
citations
affno abstractunlabeled
Small-scale spatial cognition in pigeons
Ken Cheng, Marcia L. Spetch, Debbie M. Kelly, Verner P. Bingman
2006· review· en· Behavioural Processes· Neuroscience
machine prediction:candidate · noneconsensus · none
65
citations
afffundno abstractunlabeled
Can dogs (Canis familiaris) detect human deception?
Mark Petter, Evanya Musolino, William A. Roberts, Mark R. Cole
2009· article· en· Behavioural Processes· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
58
citations
afffundno abstractunlabeled
Dogs choose a human informant: Metacognition in canines
Shannon A. McMahon, Krista Macpherson, William A. Roberts
2010· article· en· Behavioural Processes· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
47
citations
affno abstractunlabeled
A framework for the study of behavior
Jerry A. Hogan
2014· article· en· Behavioural Processes· Psychology
machine prediction:candidate · noneconsensus · none
40
citations

How this was built: Screen · Findings · About