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
Dental materials and restorations
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.

1,067 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.
1,067 works in the cohort · of 4,299,418page 18 of 22

Labels cover 0 of 1,067 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 1,067 of 1,067 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.

aboutno affunlabeled
Bond failure in clinical practice
Mark Ewing
2009· article· en· Australasian Orthodontic Journal· Dentistry
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Preventive Dental Material
Larissa Bubnowicz, Rodrigo França
2018· book-chapter· en· From biomaterials towards medical devices.· Dentistry
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Comparison of impression techniques and double pouring by dental cast’s accuracy
Aion Mangino Messias, Stephania Caroline Rodolfo Silva, Filipe de Oliveira Abi‐Rached, Raphael Freitas de Souza, José Maurício dos Santos Nunes Reis
2019· article· en· Brazilian journal of oral sciences/Brazilian Journal of Oral Sciences· Dentistry
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
Etude de la mouillabilite de l'invar par un email
Jean‐Claude Labbé, E. Q. Labrador, Pierre Lefort, Virginie Leroux
2000· article· fr· Annales de Chimie Science des Matériaux· Dentistry
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
10.1016/s0000-0000(08)53414-0
2000· article· en· Time to knit· Dentistry
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
1
citations
aboutno affunlabeled
Current evidence for IOD and IARPD
Manabu Kanazawa, Maiko Iwaki, Shunsuke Minakuchi
2021· article· en· Annals of Japan Prosthodontic Society· Dentistry
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About