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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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Computational Statistics & Data Analysis
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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
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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.

181 results · 1 filter active ·
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20002025
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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.
181 works in the cohort · of 4,299,418page 2 of 4

Labels cover 0 of 181 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 181 of 181 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
Approximate inference for disease mapping
Laurie Ainsworth, C. B. Dean
2005· article· en· Computational Statistics & Data Analysis· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
28
citations
aboutno affunlabeled
Functional archetype and archetypoid analysis
Irene Epifanio
2016· article· en· Computational Statistics & Data Analysis· Environmental Science
machine prediction:candidate · noneconsensus · none
28
citations
afffundno abstractunlabeled
Improving the performance of kurtosis estimator
Lihua An, S. Ejaz Ahmed
2007· article· en· Computational Statistics & Data Analysis· Mathematics
machine prediction:candidate · noneconsensus · none
27
citations
afffundno abstractunlabeled
Distributed adaptive Huber regression
Jiyu Luo, Qiang Sun, Wen‐Xin Zhou
2022· article· en· Computational Statistics & Data Analysis· Medicine
machine prediction:candidate · noneconsensus · none
20
citations
affno abstractunlabeled
Visualizing categorical data in ViSta
Pedro Valero‐Mora, Forrest W. Young, Michael Friendly
2003· article· en· Computational Statistics & Data Analysis· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
18
citations
affno abstractunlabeled
Ensemble classification of paired data
Werner Adler, Alexander Brenning, Sergej Potapov, Matthias Schmid, Berthold Lausen
2010· article· en· Computational Statistics & Data Analysis· Mathematics
machine prediction:candidate · noneconsensus · none
16
citations
affno abstractunlabeled
Multivariate trees for mixed outcomes
Abdessamad Dine, Denis Larocque, François Bellavance
2009· article· en· Computational Statistics & Data Analysis· Mathematics
machine prediction:candidate · noneconsensus · none
14
citations
afffundno abstractunlabeled
One-step minimum Hellinger distance estimation
Rohana J. Karunamuni, Jingjing Wu
2011· article· en· Computational Statistics & Data Analysis· Computer Science
machine prediction:candidate · noneconsensus · none
14
citations
affno abstractunlabeled
Robust estimation under progressive censoring
Indrani Basak, N. Balakrishnan
2003· article· en· Computational Statistics & Data Analysis· Mathematics
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
Parametric sensitivity: A case study comparison
Hana Sulieman, P. James McLellan
2009· article· en· Computational Statistics & Data Analysis· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations

How this was built: Screen · Findings · About