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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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Advanced Clustering Algorithms Research
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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.

421 results · 1 filter active ·
Categories
Machine labels · sparse coverage
Evidence
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
421 works in the cohort · of 4,299,418page 2 of 9

Labels cover 0 of 421 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 421 of 421 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

afffundunlabeled
Weighted Clustering
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
48
citations
affno abstractunlabeled
Subspace multi-clustering: a review
2017· review· en· Knowledge and Information Systems· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
41
citations
affunlabeled
Constraint-driven clustering
2007· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
38
citations
affunlabeled
Using Pivots to Speed-Up k-Medoids Clustering
2011· article· en· Cadernos de Linguística e Teoria da Literatura (Universidade Federal de Minas Gerais)· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
24
citations
affno abstractunlabeled
Finding multiple stable clusterings
2016· article· en· Knowledge and Information Systems· Computer Science
distilled prediction:candidate · noneconsensus · none
23
citations
affunlabeled
Document clustering with committees
2002· article· en· Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '02· Computer Science
distilled prediction:candidate · noneconsensus · none
22
citations
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How this was built: Screen · Findings · About