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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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Wildlife Ecology and Conservation
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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.

6,296 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
6,296 works in the cohort · of 4,299,418page 25 of 126

Labels cover 8 of 6,296 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 6,296 of 6,296 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
Is the endangered Grevy's zebra threatened by hybridization?
Justine E. Cordingley, Siva R. Sundaresan, Ilya R. Fischhoff, Beth Shapiro, Jennifer A. Ruskey, Daniel I. Rubenstein
2009· article· en· Animal Conservation· Environmental Science
machine prediction:candidate · noneconsensus · none
49
citations
affunlabeled
Why men trophy hunt
Chris T. Darimont, Brian F. Codding, Kristen Hawkes
2017· review· en· Biology Letters· Environmental Science
machine prediction:candidate · noneconsensus · none
49
citations
fundvenueaboutno affunlabeled
Monitoring vertebrate populations using observational data
Wesley M. Hochachka, Kathy Martin, Frank I. Doyle, Charles J. Krebs
2000· article· en· Canadian Journal of Zoology· Environmental Science
machine prediction:candidate · noneconsensus · none
47
citations
afffundaboutunlabeled
Observer aging and long‐term avian survey data quality
Robert G. Farmer, Marty L. Leonard, Joanna Mills Flemming, Sean C. Anderson
2014· article· en· Ecology and Evolution· Environmental Science
machine prediction:candidate · metaresearchconsensus · none
47
citations
afffundvenueaboutunlabeled
Moose, caribou, and fire: have we got it right yet?
Craig A. DeMars, Robert Serrouya, Matthew A. Mumma, Michael P. Gillingham, R. Scott McNay, Stan Boutin
2019· article· en· Canadian Journal of Zoology· Environmental Science
machine prediction:candidate · noneconsensus · none
47
citations
afffundunlabeled
Animal migration in the Anthropocene: threats and mitigation options
Steven J. Cooke, Morgan L. Piczak, Navinder J. Singh, Susanne Åkesson, Adam T. Ford, Shawan Chowdhury +10 more
2024· article· en· Biological reviews/Biological reviews of the Cambridge Philosophical Society· Environmental Science
machine prediction:candidate · noneconsensus · none
47
citations

How this was built: Screen · Findings · About