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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 Modeling and Causal Inference
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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.

961 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.
961 works in the cohort · of 4,299,418page 7 of 20

Labels cover 2 of 961 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 961 of 961 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
From high-level inference algorithms to efficient code
Rajan Walia, P. J. Narayanan, Jacques Carette, Sam Tobin-Hochstadt, Chung-chieh Shan
2019· article· en· Proceedings of the ACM on Programming Languages· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
First Order Probabilistic Logic
Brigitte Jaumard, Alexandre Fortin, Md. Istiaque Shahriar, Razia Sultana
2006· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
afffundno abstractunlabeled
The logic of qualitative probability
James P. Delgrande, Bryan Renne
2019· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Probabilistic n-Choose-k Models for Classification and Ranking
Kevin Swersky, Brendan J. Frey, Daniel Tarlow, Richard S. Zemel, Ryan P. Adams
2012· article· en· Digital Access to Scholarship at Harvard (DASH) (Harvard University)· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Inferences from prior-based loss functions
Michael Evans, Gun Ho Jang
2011· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
afffundunlabeled
Situation Calculus Semantics for Actual Causality
Vitaliy Batusov, Mikhail Soutchanski
2018· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Exponential Models: Approximations for Probabilities
D. A. S. Fraser, Ali Naderi, Kexin Ji, Wei Lin, Jie Su
2011· article· en· Journal of the Iranian Statistical Society· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
PIS: a probabilistic inference system
Keith C. C. Chan, Andrew K. C. Wong
2003· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Approximate reasoning by pairwise comparisons
Tamar Kakiashvili, Waldemar W. Koczkodaj, Jean-Pierre Magnot
2017· review· en· Physics of Life Reviews· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Classification Methods
Aijun An
2009· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Pushing Random Walk Beyond Golden Ratio
Ehsan Amiri, Evgeny Skvortsov
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
fundno affunlabeled
An automated classification algorithm for multiwavelength data
Yanxia Zhang, A-Li Luo, Yongheng Zhao
2004· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations

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