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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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Fuzzy Systems and Optimization
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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.

170 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.
170 works in the cohort · of 4,299,418page 1 of 4

Labels cover 0 of 170 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 170 of 170 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.

afffundno abstractunlabeled
Binary option pricing using fuzzy numbers
A. Thavaneswaran, S.S. Appadoo, Julieta Frank
2012· article· en· Applied Mathematics Letters· Mathematics
machine prediction:candidate · noneconsensus · none
56
citations
affno abstractunlabeled
Functions defined on a set of Z-numbers
Rafik Aziz Aliev, Witold Pedrycz, O. H. Huseynov
2017· article· en· Information Sciences· Mathematics
machine prediction:candidate · noneconsensus · none
55
citations
afffundno abstractunlabeled
Option valuation model with adaptive fuzzy numbers
K. Thiagarajah, S. S. Appadoo, A. Thavaneswaran
2007· article· en· Computers & Mathematics with Applications· Mathematics
machine prediction:candidate · noneconsensus · none
54
citations
affno abstractunlabeled
Fuzzy matrix games via a fuzzy relation approach
V. Vijay, Apurv Mehra, S. Chandra, C. R. Bector
2007· article· en· Fuzzy Optimization and Decision Making· Mathematics
machine prediction:candidate · noneconsensus · none
47
citations
affno abstractunlabeled
Regularized fuzzy clusterwise ridge regression
Hye Won Suk, Heungsun Hwang
2009· article· en· Advances in Data Analysis and Classification· Mathematics
machine prediction:candidate · noneconsensus · none
16
citations
affno abstractunlabeled
On the rectangular fuzzy complex linear systems
M. Ghanbari, Tofigh Allahviranloo, Witold Pedrycz
2020· article· en· Applied Soft Computing· Mathematics
machine prediction:candidate · noneconsensus · none
15
citations
afffundno abstractunlabeled
Supermodular Functions on Finite Lattices
S. David Promislow, Virginia R. Young
2005· article· en· Order· Mathematics
machine prediction:candidate · noneconsensus · none
13
citations

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