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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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ASCILITE Publications
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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
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aboutaboutness

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

26 results · 1 filter active ·
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20062025
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Categories
Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
26 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 26 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 26 of 26 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
Using technology to encourage self-directed learning
Shane Dawson, Leah P. Macfadyen, Evan F. Risko, Tom Foulsham, Alan Kingstone
2012· article· en· ASCILITE Publications· Psychology
machine prediction:candidate · noneconsensus · none
10
citations
aboutno affunlabeled
Academic integrity compliance and education
Margaret Hamilton, Joan Richardson
2008· article· en· ASCILITE Publications· Social Sciences
machine prediction:candidate · research_integrityconsensus · none
4
citations
affunlabeled
iTeach, iDance
Nathaniel Ostashewski, Doug Reid
2010· article· en· ASCILITE Publications· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
fundno affunlabeled
From digital natives to digital literacy
Erika E. Smith, Renate Kahlke, Terry Judd
2018· article· en· ASCILITE Publications· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
From neural to social
Shane Dawson, Leah P. Macfadyen, Lori Lockyer, David Mazzochi-Jones
2010· article· en· ASCILITE Publications· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Using mobile technology for workplace learning
Franziska Trede, Susie Macfarlane, Lina Markauskaitė, Peter Goodyear, Celina McEwen, Freny Tayebjee
2016· article· en· ASCILITE Publications· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Aiming for the right place
Cathy Gunn, Josephine Csete, John Barnett
2009· article· en· ASCILITE Publications· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

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