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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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Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
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Retraction
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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.

18 results · 1 filter active ·
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20112024
Publication date
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
18 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 18 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 18 of 18 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
Density‐based clustering
Hans‐Peter Kriegel, Peer Kröger, Jörg Sander, Arthur Zimek
2011· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Computer Science
machine prediction:candidate · noneconsensus · none
810
citations
affunlabeled
Density‐based clustering
Ricardo J. G. B. Campello, Peer Kröger, Jörg Sander, Arthur Zimek
2019· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Computer Science
machine prediction:candidate · noneconsensus · none
116
citations
affunlabeled
Smart city and resilient city: Differences and connections
Shi‐Yao Zhu, Dezhi Li, Haibo Feng, Tiantian Gu, Kasun Hewage, Rehan Sadiq
2020· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Engineering
machine prediction:candidate · noneconsensus · none
62
citations
affunlabeled
Mining uncertain data
Carson K. Leung
2011· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Computer Science
machine prediction:candidate · noneconsensus · none
59
citations
affunlabeled
Rough clustering
Pawan Lingras, Georg Peters
2011· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Computer Science
machine prediction:candidate · noneconsensus · none
51
citations
affunlabeled
Bayesian treed response surface models
Hugh Chipman, Edward I. George, Robert B. Gramacy, Robert McCulloch
2013· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Mathematics
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Introducing WIREs Data Mining and Knowledge Discovery
Witold Pedrycz
2011· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
8
citations

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