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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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Data Analysis with R
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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.

814 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.
814 works in the cohort · of 4,299,418page 1 of 17

Labels cover 3 of 814 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 814 of 814 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
Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Douglas M. Bates, Martin Mächler, Benjamin M. Bolker, Steve Walker
2015· article· en· Journal of Statistical Software· Computer Science
machine prediction:candidate · noneconsensus · none
85,618
citations
affunlabeled
Visualization in Bayesian Workflow
Jonah Gabry, Daniel Simpson, Aki Vehtari, Michael Betancourt, Andrew Gelman
2019· article· en· Journal of the Royal Statistical Society Series A (Statistics in Society)· Computer Science
machine prediction:candidate · noneconsensus · none
1,128
citations
affunlabeled
Fast and wild: Bootstrap inference in Stata using boottest
David Roodman, Morten Ørregaard Nielsen, James G. MacKinnon, Matthew D. Webb
2019· article· en· The Stata Journal Promoting communications on statistics and Stata· Computer Science
machine prediction:candidate · noneconsensus · none
884
citations
affno abstractunlabeled
BoxPlotR: a web tool for generation of box plots
Michaela Spitzer, Jan Wildenhain, Juri Rappsilber, Mike Tyers
2014· letter· en· Nature Methods· Computer Science
machine prediction:candidate · noneconsensus · none
875
citations
affaboutunlabeled
Web Site and R Package for Computing E-values
Maya B. Mathur, Peng Ding, Corinne A. Riddell, Tyler J. VanderWeele
2018· article· en· Epidemiology· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
755
citations
affunlabeled
A review of spline function procedures in R
Aris Perperoglou, Willi Sauerbrei, Michał Abrahamowicz, Matthias Schmid
2019· review· en· BMC Medical Research Methodology· Computer Science
machine prediction:candidate · noneconsensus · none
577
citations
affunlabeled
Ten Simple Rules for Effective Statistical Practice
Robert E. Kass, Brian Caffo, Marie Davidian, Xiao‐Li Meng, Bin Yu, Nancy Reid
2016· editorial· en· PLoS Computational Biology· Computer Science
machine prediction:candidate · metaresearchconsensus · metaresearch
116
citations
fundno affunlabeled
Nonparametric Econometrics: The np Package
Tristen Hayfield, Jeffrey S. Racine
2008· article· en· Repository for Publications and Research Data (ETH Zurich)· Computer Science
machine prediction:candidate · noneconsensus · none
100
citations
afffundunlabeled
Interpretable dimension reduction
Hugh Chipman, Hong Gu
2005· article· en· Journal of Applied Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
62
citations
affunlabeled
Using the R Commander
John P. Fox
2016· book· en· Computer Science
machine prediction:candidate · noneconsensus · none
32
citations
affno abstractunlabeled
Quantitative Methods for the Social Sciences
Daniel Stockemer, Jean‐Nicolas Bordeleau
2023· book· en· Springer texts in political science and international relations· Computer Science
machine prediction:candidate · noneconsensus · none
29
citations
affno abstractunlabeled
Programming in R
Pierre Lafaye de Micheaux, Rémy Drouilhet, Benoît Liquet
2013· book-chapter· en· Statisctics and computing/Statistics and computing· Computer Science
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
ChrontouR
2020· article· en· OSF Preprints (OSF Preprints)· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
venueno affno abstractunlabeled
10.1016/0967-0653(93)94868-y
2000· article· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
17
citations
affunlabeled
A quality framework for statistical algorithms
Wesley Yung, Siu‐Ming Tam, Bart Buelens, Hugh Chipman, Florian Dumpert, Gabriele Ascari +3 more
2021· article· en· Statistical Journal of the IAOS· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
venueno affno abstractunlabeled
Multistate Analysis of Life Histories with R
David A. Swanson
2015· article· en· Canadian Studies in Population· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations

How this was built: Screen · Findings · About