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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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Semantic Web and Ontologies
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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.

1,983 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.
1,983 works in the cohort · of 4,299,418page 23 of 40

Labels cover 1 of 1,983 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 1,983 of 1,983 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
Object and Relations Uncertainty
Tony Francolini
2012· article· en· Academy of Management Proceedings· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
The Two-Variable Situation Calculus
Yilan Gu, Mikhail Soutchanski
2006· article· en· Starting AI Researchers' Symposium· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Knowledge Signatures for Information Integration
J. Thomson, Andrew Cowell, Patrick Paulson, Scott Butner, Mark Whiting
2004· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
LCSH and Environmental Science
F. M. Purcell, Julia Bullard
2023· article· en· Nordic Journal of Library and Information Studies· Computer Science
machine prediction:candidate · scholarly_communicationconsensus · none
1
citations
affunlabeled
Reducible Theories and Amalgamations of Models
Bahar Aameri, Michael Grüninger
2022· article· en· ACM Transactions on Computational Logic· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Semantic Similarity Functions and Their Applications
Yang Liu, Alaa Alsaig, V. S. Alagar
2024· book-chapter· en· Communications in computer and information science· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Semantic Web Services for Healthcare
Christina Catley, Monique Frize, Dorina C. Petriu
2011· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affvenueunlabeled
Linked Metadata and New Discoveries
Julienne Pascoe
2015· article· en· Scholarly and Research Communication· Computer Science
machine prediction:candidate · scholarly_communicationconsensus · none
1
citations
affno abstractunlabeled
Tagging and Fuzzy Sets
Ronald R. Yager, Marek Reformat
2010· book-chapter· en· Studies in computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About