MétaCan
Menu
Cohort builder

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.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Topic
Financial Risk and Volatility Modeling
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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
aboutaboutness

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

1,344 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
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 16 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 teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Un contre-exemple à une conjecture de Hutchinson et Lai
Patrick Munroe, Thomas Ransford, Christian Genest
2010· article· fr· Comptes Rendus Mathématique· Economics, Econometrics and Finance
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
3
citations
venueno affunlabeled
A New Proxy for Estimating the Roughness of Volatility
Qi Zhao, Alexandra Chronopoulou
2024· article· en· Journal of risk and financial management· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
3
citations
afffundno abstractunlabeled
Testing for Equality between Two Copulas
Bruno Rémillard, Olivier Scaillet
2007· article· en· Journal of Multivariate Analysis· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
3
citations
fundno affunlabeled
Information Content of Volatility Forecasts at Medium-term Horizons
John W. Galbraith, Turgut Kıṣınbay
2002· preprint· en· Érudit documents and data repository (Érudit Consortium, University of Montreal)· Economics, Econometrics and Finance
distilled prediction:candidate · metaepi_narrowconsensus · none
3
citations
affunlabeled
Computational Challenges of t and Related Copulas
Erik Hintz, Marius Hofert, Christiane Lemieux
2022· article· en· Journal of Data Science· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
3
citations
afffundno abstractunlabeled
Copula-based conditional tail indices
Vincenzo Coia, Harry Joe, Natalia Nolde
2023· article· en· Journal of Multivariate Analysis· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
2
citations
afffundno abstractunlabeled
Zero-modified count time series with Markovian intensities
N. Balakrishna, P. Muhammed Anvar, Bovas Abraham
2023· article· en· Journal of Statistical Planning and Inference· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Copulae: On the Crossroads of Mathematics and Economics
Wolfgang Karl Härdle, Piotr Marek Jaworski, Johanna Nešlehová
2016· article· en· Oberwolfach Reports· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About