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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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Statistical Methods and 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.

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.

1,935 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.
1,935 works in the cohort · of 4,299,418page 20 of 39

Labels cover 22 of 1,935 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 1,935 of 1,935 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.

fundno affunlabeled
Information criteria for non-normalized models
Takeru Matsuda, Masatoshi Uehara, Aapo Hyvärinen
2019· preprint· en· arXiv (Cornell University)· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
afffundunlabeled
Bootstrap Inference for Group Factor Models
Śılvia Gonçalves, Benoît Perron
2024· article· en· Journal of Financial Econometrics· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
fundno affunlabeled
The Subcluster Wild Bootstrap for Few (Treated) Clusters
James G. MacKinnon, Matthew D. Webb
2016· preprint· en· Carleton University's Institutional Repository (MacOdrum Library, Carleton University)· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
venueaboutno affunlabeled
Kernel density estimation with Berkson error
James P. Long, Noureddine El Karoui
2016· article· en· Canadian Journal of Statistics· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Survival analysis following dynamic randomization
Xiaolong Luo, Mingyu Li, Gongjun Xu, Dongsheng Tu
2016· article· en· Contemporary Clinical Trials Communications· Mathematics
machine prediction:candidate · metaresearchconsensus · none
3
citations
affunlabeled
Multiple change‐point models for time series
Ian B. MacNeill, Venkata K. Jandhyala, Abhishek Kaul, S. Fotopoulos
2019· article· en· Environmetrics· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
venueaboutno affunlabeled
Combined composite likelihood
Euloge Clovis Kenne Pagui, Alessandra Salvan, Nicola Sartori
2014· article· en· Canadian Journal of Statistics· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
The XGTDL family of survival distributions
Gilbert MacKenzie, Milica Bucknall, Yasin Al-tawarah, Defen Peng
2021· article· en· Japanese Journal of Statistics and Data Science· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
venueaboutno affgpt · no categorygrok · no categoryopus · no categorymodels agree
A component lasso
Nadine Hussami, Robert Tibshirani
2015· article· en· Canadian Journal of Statistics· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations

How this was built: Screen · Findings · About