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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.

affaffiliation
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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 9 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 teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Logistic Markov Decision Processes
Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu
2017· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Matching and Ranking Trustworthy Context-Dependent Universities
Wadee Alhalabi, A. Salim Bawazir, Mubarak Mohammad, Akila Sarirete
2017· article· en· International Journal on Semantic Web and Information Systems· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
4
citations
affunlabeled
Building an effective groupware system
Mohammed Abdel Razek, Claude Frasson, Marc Kaltenbach
2004· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Deep Learning Methods for Query Auto Completion
Manish Gupta, Meghana Joshi, Puneet Agrawal
2023· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
4
citations
affunlabeled
Time aware topic based recommender system
Emad Gohari Boroujerdi, Heidar Davoudi, Aijun An, Elnaz Delpisheh
2016· article· en· Big Data and Information Analytics· Computer Science
distilled prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Chiron: A Robust Recommendation System with Graph Regularizer
Saber Shokat Fadaee, Mohammad Sajjad Ghaemi, Hossein Azari Soufiani, Ravi Sundaram
2017· preprint· en· Advances in intelligent systems and computing· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
3
citations
affunlabeled
AI in Personalized Product Recommendations
Kartik Hosanagar, Dokyun Lee
2023· article· en· Management and business review.· Computer Science
distilled prediction:candidate · noneconsensus · none
3
citations
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