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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.

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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.

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Flood Risk Assessment and Management
Retraction
Abstract
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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.

1,552 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,552 works in the cohort · of 4,299,418page 24 of 32

Labels cover 2 of 1,552 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 1,552 of 1,552 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.

afffundvenueaboutunlabeled
Duckling mortality at a river weir
Stewart B. Rood, Amber Willcocks
2019· article· en· The Canadian Field-Naturalist· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Major Floods
2010· report· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
A cold-region flood model framework for Canada
Srinivas Kondapalli, K. A. Sawicz, Matthew Hergott, Xing Zheng, Samyadeep Ghosh, Manu Vyas +3 more
2025· article· en· Hydrological Sciences Journal· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Reply on RC2
Heidi Kreibich
2023· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
afffundunlabeled
Comment on essd-2022-330
2023· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affunlabeled
INSYDE-BI: A Flood Damage Model for Residential Buildings in Burundi
Cyriaque Bizimana, Mario Di Bacco, Anna Rita Scorzini
2024· article· en· Proceedings of the International Conference on Civil, Structural and Transportation Engineering· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
The British Columbia Federationist
2017· article· en· Open Collections· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
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