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
Market Dynamics and Volatility
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.

2,530 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.
2,530 works in the cohort · of 4,299,418page 44 of 51

Labels cover 4 of 2,530 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 2,530 of 2,530 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.

affunlabeled
Fees and Ticks
Maha Khan Phillips
2015· article· en· CFA Magazine· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Disentangling India’s Investment Slowdown
Rahul Anand, Volodymyr Tulin
2014· preprint· en· RePEc: Research Papers in Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Understanding Order-Flow Volatility
Rahul Ravi
2014· article· en· International Journal of Financial Management· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Oil price volatility and stock returns in the G7 economies
Elena María Díaz, Juan Carlos Molero, Fernando Pérez de Gracia
2016· preprint· en· RePEc: Research Papers in Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Commodity Price Forecasts, Futures Prices and Pricing Models
Gonzalo Cortázar, Cristobal Millard, Eduardo S. Schwartz, Hector Ortega
2016· article· en· RePEc: Research Papers in Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Episodic Nonlinearity in Leading Global Currencies
Apostolos Serletis, A. G. Malliaris, Melvin Hinich, Periklis Gogas
2010· preprint· en· RePEc: Research Papers in Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Weather, Mood and Stock Market Returns in Argentina
Bakri Abdul Karim, Muhammad Hafiz Mohd Shukri, Sharon Tay Chyu Yuin
2018· article· en· Accounting and Finance Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Counter-Evidence of ASEAN Stock Market Efficiency
Abdul Razak Abdul Hadi
2015· article· en· International Journal of Economics and Finance· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Oil Demand and Stocks
2025· article· en· Oil and Energy Trends· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Forecasting Oil Prices: A Comparative Study
Jihad El Hokayem, Joseph Gemayel, Dany Mezher
2022· article· en· International Journal of Economics and Finance· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About