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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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Canadian Journal of Statistics
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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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venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

1,050 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.
1,050 works in the cohort · of 4,299,418page 17 of 21

Labels cover 18 of 1,050 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 1,050 of 1,050 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.

afffundvenueaboutunlabeled
A stochastic graph process for epidemic modelling
Yasaman Hosseinkashi, Shojaeddin Chenouri, Christopher G. Small, Rob Deardon
2012· article· en· Canadian Journal of Statistics· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations
venueaboutno affunlabeled
Robust location estimation with missing data
Mariela Sued, Vı́ctor J. Yohai
2012· preprint· en· Canadian Journal of Statistics· Mathematics
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Automatic sparse principal component analysis
Heewon Park, Rui Yamaguchi, Seiya Imoto, Satoru Miyano
2020· article· en· Canadian Journal of Statistics· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
affvenueunlabeled
Marginally restricted sequential D‐optimal designs
Jesús López–Fidalgo, Raúl Martín Martín, Douglas P. Wiens
2008· article· en· Canadian Journal of Statistics· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
afffundvenueaboutunlabeled
Price bias and common practice in option pricing
Jean‐François Bégin, Geneviève Gauthier
2019· article· en· Canadian Journal of Statistics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About