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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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Education Systems 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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venuejournal
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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.

2,366 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.
2,366 works in the cohort · of 4,299,418page 23 of 48

Labels cover 4 of 2,366 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 2,366 of 2,366 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
Why Did I Stay So Long
Randy Vlasin
2007· article· en· ˜The œAgricultural education magazine· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Track of GPS-Drifter M184_65-1 (Drifter_217)
2024· dataset· en· Publishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
You know you're a rural resident when...
Jonathan R. Kerr, Van Aerde T, G Woollam, A Jongerius
2007· article· fr· PubMed· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Contemporary Challenges Teaching Labour History
Mark Leier, John‐Henry Harter, Dale M. McCartney, Andrea Samoil
2019· article· en· Labour / Le Travail· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Engaging the Local Community: Why Bother?
Mary Carlsen
2008· article· en· Intersections Canadian Journal of Music· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractgemma · no categorygpt · no categorymodels split
Successful rural rotation: what do learners look for?
Kerr, Neary Jd, Hartwick Kr, Van Aerde T
2006· article· fr· PubMed· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
What I Like About the Course
Jeff Ross
2012· article· en· Divergent/Convergent· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About