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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.

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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Forest Management and Policy
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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
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

2,661 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.
2,661 works in the cohort · of 4,299,418page 40 of 54

Labels cover 7 of 2,661 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 2,661 of 2,661 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
Centre du Quebec Forest Plots
Dylan Craven
2019· dataset· en· Figshare· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Frontmatter
2001· book-chapter· en· University of Toronto Press eBooks· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
fundvenueaboutno affunlabeled
University News / Nouvelles des Universités
Phil Cooze, Seth Cain, Jen Maccormick, Verna Crossman, Holly Aggas, Ken Forsythe +3 more
2002· article· fr· The Forestry Chronicle· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
The Triad - History and Experience
Robert S. Seymour
2025· article· DigitalCommons (California Polytechnic State University)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
YorkU.forest.Oct5-2016
Virdi Amrit, Grant Nyiesha, Wasson Jasleen
2016· article· en· Figshare· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Forest-based Care Market Outlook
Cecilia Fraccaroli, Annebel Soer, Ilaria Doimo, Rik De Vreese, Tahia Devisscher, Monika Humer +3 more
2021· report· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Sectoral Uncertainty
2022· article· en· Econstor (Econstor)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About