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
Coral and Marine Ecosystems Studies
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.

2,134 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.
2,134 works in the cohort · of 4,299,418page 42 of 43

Labels cover 5 of 2,134 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 2,134 of 2,134 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
Marine Communities
Paul V. R. Snelgrove
2015· other· en· Encyclopedia of Life Sciences· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Ocean grabbing
Nathan Bennett, Hugh Govan, Terre Satterfield
2018· preprint· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Corals in the Anthropocene
Irus Braverman
2018· book-chapter· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Biogeography: A deep dive on reefs
Peter F. Sale
2023· letter· en· Current Biology· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.1016/0967-0653(96)84992-1
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Marine and Coastal Resources
Isa Olalekan Elegbede, Vanessa MaxemilieNgo-Massou, Fátima Kies, Deepeeka Kaullysing, Saud M. Al Jufaili, Ayodele Oloko
2023· book-chapter· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Coral Reef and Other Tropical Fisheries
Villy Christensen, Daniel Pauly, Xiaojia He
2018· book-chapter· en· Elsevier eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(98)85990-5
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Little bites out of a big reef problem
M. Aaron MacNeil
2025· letter· en· Proceedings of the National Academy of Sciences· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Gear and Habitat Modulate Fishing Effects on Coral Reef Fishes
Felipe Carvalho, Michael Power, Beatrice Padovani Ferreira, Eduardo G. Martins, Leandro Castello
2024· preprint· en· SSRN Electronic Journal· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)95032-x
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)89418-5
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(96)80513-z
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About