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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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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.

849 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.
849 works in the cohort · of 4,299,418page 17 of 17

Labels cover 1 of 849 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 849 of 849 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.

affno abstractunlabeled
Mobile Recommendation
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Recommendation Systems
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Recommendation Systems
Professor Reda Alhajj, Professor Jon Rokne
2014· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Collaborative Recommendation
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Knowledge Cafe and Gelateria
Nicole C. L. Noel, Michelle Nevett
2018· article· en· Scholarship at UWindsor (University of Windsor)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Microblogging Data
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Tag-Based Recommender Systems
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Social Navigation for Learning in Immersive Worlds
Jon Dron
2013· book-chapter· en· Integrated series on information systems/Integrated series in information systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Affective Recommender Systems
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Modeling Temporal User Interests
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Create a Profile for User Using Web Usage Mining
Zeinab khademali, Nima Attarzadeh, Mohammad Mehdi LotfiNejad
2013· article· en· Journal of academic and applied studies· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Successive POI Recommendation
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
The recommender problem with convex hulls
Marie‐Laure Bougnol, José H. Dulá
2024· article· en· INFOR Information Systems and Operational Research· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
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