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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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Forest ecology and management
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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.

2,856 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.
2,856 works in the cohort · of 4,299,418page 52 of 58

Labels cover 5 of 2,856 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 2,856 of 2,856 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
Some aspects of forestry in B.C.
F Knapp
2009· article· en· Open Collections· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
The Canadian Forest
2003· book-chapter· en· McGill-Queen's University Press eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
fundaboutno affunlabeled
Wood formation in black spruce :
Carlo Lupi
2012· book· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Climate and the growth of lodgepole pine in Alberta
Victor J. Lieffers, Edward H. Hogg, Sophan Chhin, Shengxiang Huang
2008· article· en· University of Alberta Library· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
The pace of life for forest trees
2024· article· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Tree Rings in common garden Experiments (T-REX)
Martin P. Girardin, Nathalie Isabel, Xiaojing Guo, Manuel Lamothe, Isabelle Duchesne, P. Lenz
2020· dataset· en· Figshare· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
coin-or/SYMPHONY: Release releases/5.7.3
2025· other· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Orange show in San Bernardino, 1956
2021· dataset· en· University of Southern California Digital Library· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
fundaboutno affunlabeled
Growth and productivity of black spruce (
2010· article· en· Springer Link (Chiba Institute of Technology)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Tree Support Measures
Edward Susko
2024· book-chapter· en· Elsevier eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Terra umana
2007· other· it· HAL (Le Centre pour la Communication Scientifique Directe)· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
The Child and Parent Emotion Study
2022· dataset· en· Australian Data Archive· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Understanding Natural Forest Diebacks
Philip J. Burton
2014· article· en· Journal of Forestry· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
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