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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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Financial Risk and Volatility Modeling
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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.

1,344 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.
1,344 works in the cohort · of 4,299,418page 26 of 27

Labels cover 1 of 1,344 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 1,344 of 1,344 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
Introduction to the Issue on High Frequency Econometrics
Lukas Bauer, Roxana Halbleib, Richard Olsen, Torben G. Andersen, Ingmar Nolte
2025· article· en· Journal of Econometrics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Clustered Archimax copulas
Simon Chatelain, Samuel Perreault, Anne‐Laure Fougères, Johanna Nešlehová
2025· article· en· Electronic Journal of Statistics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Geometric modelling of spatial extremes
Lydia Kakampakou, Jennifer L. Wadsworth
2025· preprint· arXiv (Cornell University)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Challenges in Implementing Worst-Case Analysis
Jón Danı́elsson, Lerby Murat Ergun, Casper G. de Vries
2017· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Maximum Likelihood
Jin‐Chuan Duan, Andras Fulop
2004· other· en· Encyclopedia of Actuarial Science· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Emerging Markets Reward Risk
Salim Lahmiri, Stéphane Gagnon
2016· article· en· International Journal of Innovation in the Digital Economy· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Adaptive Realized Kernels
Marine Carrasco, Rachidi Kotchoni
2011· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Asymptotic multivariate expectiles
Véronique Maume‐Deschamps, Didier Rullière, Khalil Said
2017· preprint· en· arXiv (Cornell University)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Negative Binomial Autoregressive Process
Yang Lu, Christian Gouriéroux
2018· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About