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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 41 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
A Guide for Virginia's Forest Landowners
John F. Munsell, Jennifer L. Gagnon
2011· article· en· VTechWorks (Virginia Tech)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Carbon Budget Model
Roberto Pilli, Giacomo Grassi
2018· other· en· Joint Research Centre (European Commission)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
by
2007· article· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Canadian forest and land policy.
Albert Desjardins
2013· article· en· Deep Blue (University of Michigan)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
56008: The Sisters Buried at Lemnos
2024· other· en· University of Oxford· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Branchlines. Volume 22, number 2
2011· article· en· Open Collections· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Branchlines. Volume 13, number 1
2012· article· en· Open Collections· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
Forest Policy Issues Forum
2004· article· en· The Forestry Chronicle· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affno abstractunlabeled
Canadian Journal of Forest Research: Table of Contents
Andreas Rothe, Dan Binkley, Robert I. Griffiths, Alan Swanson, Kwan‐Soo Woo, Lauren Fins +16 more
2001· article· en· The Forestry Chronicle· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About