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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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Bayesian Methods and Mixture Models
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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.

1,238 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.
1,238 works in the cohort · of 4,299,418page 3 of 25

Labels cover 4 of 1,238 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 1,238 of 1,238 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.

afffundunlabeled
Bayesian Analysis of Dyadic Data
Paramjit Gill, Tim B. Swartz
2007· article· en· American Journal of Mathematical and Management Sciences· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
affno abstractunlabeled
Copula analysis of mixture models
Mathieu Vrac, Lynne Billard, Edwin Diday, A. Chédin
2011· article· en· Computational Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
affunlabeled
Non-Local Manifold Parzen Windows
Yoshua Bengio, Hugo Larochelle, Pascal Vincent
2005· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
47
citations
affunlabeled
Functional mixture regression
Fang Yao, Yuejiao Fu, Thomas C. M. Lee
2010· article· en· Biostatistics· Computer Science
machine prediction:candidate · noneconsensus · none
47
citations
affunlabeled
From fields to trees
Firas Hamze, Nando de Freitas
2004· article· en· Uncertainty in Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
45
citations
afffundno abstractunlabeled
Model selection for discrete regular vine copulas
Anastasios Panagiotelis, Claudia Czado, Harry Joe, Jakob Stöber
2016· article· en· Computational Statistics & Data Analysis· Computer Science
machine prediction:candidate · noneconsensus · none
41
citations
affunlabeled
Randomized Optimum Models for Structured Prediction
Daniel Tarlow, Ryan P. Adams, Richard S. Zemel
2012· article· en· Digital Access to Scholarship at Harvard (DASH) (Harvard University)· Computer Science
machine prediction:candidate · noneconsensus · none
40
citations

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