MétaCan
ENFR
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.

Export CSVExport JSONAPI query

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
Dialogues in Clinical Neuroscience
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.

21 results · 1 filter active ·
Results by year
20012025
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.
21 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 21 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 21 of 21 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.

affunlabeled
Human intelligence and brain networks
Roberto Colom, Sherif Karama, Rex E. Jung, Richard J. Haier
2010· article· en· Dialogues in Clinical Neuroscience· Neuroscience
machine prediction:candidate · noneconsensus · none
319
citations
affunlabeled
Facts and myths pertaining to fibromyalgia
Winfried Häuser, Mary‐Ann Fitzcharles
2018· review· en· Dialogues in Clinical Neuroscience· Medicine
machine prediction:candidate · noneconsensus · none
215
citations
affunlabeled
Memory as a new therapeutic target
Karim Nader, Oliver Hardt, Ruth A. Lanius
2013· article· en· Dialogues in Clinical Neuroscience· Neuroscience
machine prediction:candidate · noneconsensus · none
67
citations
affunlabeled
Genetics in schizophrenia: where are we and what next?
Arun K. Tiwari, Clement C. Zai, Daniel J. Müller, James L. Kennedy
2010· article· en· Dialogues in Clinical Neuroscience· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
60
citations
affunlabeled
Graph theory in paediatric epilepsy: A systematic review
Raffaele Falsaperla, Giovanna Vitaliti, Simona Domenica Marino, Andrea D. Praticò, Janette Mailo, Michela Spatuzza +3 more
2021· review· en· Dialogues in Clinical Neuroscience· Neuroscience
machine prediction:candidate · noneconsensus · none
35
citations
affunlabeled
Cognitive toxicity of drugs used in the elderly
Lisa L. von Moltke, David J. Greenblatt, Myroslava K. Romach, Edward M. Sellers
2001· article· en· Dialogues in Clinical Neuroscience· Medicine
machine prediction:candidate · noneconsensus · none
15
citations

How this was built: Screen · Findings · About