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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.

affaffiliation
fundfunder
venuejournal
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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 1 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.

affno abstractunlabeled
An Introduction to MCMC for Machine Learning
Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan
2003· article· en· Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
2,418
citations
affunlabeled
Sequential Monte Carlo Samplers
Pierre Del Moral, Arnaud Doucet, Ajay Jasra
2006· article· en· Journal of the Royal Statistical Society Series B (Statistical Methodology)· Computer Science
machine prediction:candidate · noneconsensus · none
1,702
citations
afffundno abstractunlabeled
Annealed importance sampling
Radford M. Neal
2001· article· en· Statistics and Computing· Computer Science
machine prediction:candidate · noneconsensus · none
1,225
citations
fundno affno abstractunlabeled
Permutation Methods
Paul W. Mielke, Kenneth J. Berry
2001· book· en· Springer series in statistics· Computer Science
machine prediction:candidate · noneconsensus · none
353
citations
fundno affunlabeled
Combining Mixture Components for Clustering
Jean-Patrick Baudry, Adrian E. Raftery, Gilles Celeux, Kenneth Lo, Raphaël Gottardo
2010· article· en· Journal of Computational and Graphical Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
348
citations
afffundvenueaboutunlabeled
A mixture of generalized hyperbolic distributions
Ryan P. Browne, Paul D. McNicholas
2015· article· en· Canadian Journal of Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
188
citations
afffundunlabeled
Mixtures of Shifted AsymmetricLaplace Distributions
Brian C. Franczak, Ryan P. Browne, Paul D. McNicholas
2014· article· en· IEEE Transactions on Pattern Analysis and Machine Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
168
citations
afffundvenueaboutunlabeled
Model‐based clustering of longitudinal data
Paul D. McNicholas, Thomas Brendan Murphy
2010· article· en· Canadian Journal of Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
146
citations
venueno affunlabeled
Estimating the number of clusters
Antonio Cuevas, Manuel Febrero–Bande, Ricardo Fraiman
2000· article· en· Canadian Journal of Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
124
citations
affno abstractunlabeled
Counting connected graphs inside-out
Boris Pittel, Nicholas Wormald
2004· article· en· Journal of Combinatorial Theory Series B· Computer Science
machine prediction:candidate · noneconsensus · none
108
citations
affunlabeled
Likelihood Asymptotics
Ib M. Skovgaard
2001· article· en· Scandinavian Journal of Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
106
citations
affunlabeled
Hidden Markov models: Pitfalls and opportunities in ecology
Richard Glennie, Timo Adam, Vianey Leos‐Barajas, Théo Michelot, Theoni Photopoulou, Brett T. McClintock
2022· article· en· Methods in Ecology and Evolution· Computer Science
machine prediction:candidate · noneconsensus · none
101
citations
affunlabeled
Testing for a Finite Mixture Model with Two Components
Hanfeng Chen, Jiahua Chen, John D. Kalbfleisch
2003· article· en· Journal of the Royal Statistical Society Series B (Statistical Methodology)· Computer Science
machine prediction:candidate · noneconsensus · none
98
citations

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