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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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Journal of Veterinary Medical Education
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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.

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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.

1,932 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.
1,932 works in the cohort · of 4,299,418page 16 of 39

Labels cover 10 of 1,932 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 1,932 of 1,932 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.

venueno affunlabeled
Factors Influencing Seminar Learning and Academic Achievement
Annemarie Spruijt, Jimmie Leppink, Ineke H. A. P. Wolfhagen, Harold G. J. Bok, Tim Mainhard, Albert Scherpbier +2 more
2015· article· en· Journal of Veterinary Medical Education· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
9
citations
venueno affunlabeled
How to Teach Pet Loss to Veterinary Students
Susan Phillips Cohen
2008· article· en· Journal of Veterinary Medical Education· Health Professions
machine prediction:candidate · noneconsensus · none
9
citations
venueno affunlabeled
The Return on Investment in Online Education
Tana M Bishop
2007· article· en· Journal of Veterinary Medical Education· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
venueno affunlabeled
Specifications Grading for Veterinary Medicine
Erik H. Hofmeister, Philippa Gibbons, Katherine Fogelberg, Bobbi J. Conner
2022· article· en· Journal of Veterinary Medical Education· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
venueno affunlabeled
Fifty Years in the Life of Veterinary Students
Lisa M. Greenhill, R.G. Elmore, Sherry M. Stewart, K. Paige Carmichael, Michael J. Blackwell
2015· article· en· Journal of Veterinary Medical Education· Health Professions
machine prediction:candidate · noneconsensus · none
9
citations
venueno affunlabeled
The Power of Information
André J. Nault, Henry J. Baker
2011· article· en· Journal of Veterinary Medical Education· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
9
citations
venueno affunlabeled
Veterinarians in Biomedical Research: Building National Capacity
Daryl D. Buss, Michael L. Atchison, Kara N. Corps, Lauren B. Falkowski, James G. Fox, Joan C. Hendricks +3 more
2009· article· en· Journal of Veterinary Medical Education· Health Professions
machine prediction:candidate · metaresearchconsensus · none
8
citations
venueno affunlabeled
Zoological Medicine and Public Health
Bruno B. Chomel, Bennie I. Osburn
2006· article· en· Journal of Veterinary Medical Education· Medicine
machine prediction:candidate · noneconsensus · none
8
citations
venueno affunlabeled
On the Self-Renewal of Teachers
David J. Waters, Lane S. Waters
2011· article· en· Journal of Veterinary Medical Education· Health Professions
machine prediction:candidate · noneconsensus · none
8
citations

How this was built: Screen · Findings · About