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
Forecasting Techniques and Applications
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.

497 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.
497 works in the cohort · of 4,299,418page 4 of 10

Labels cover 0 of 497 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 497 of 497 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

venueno affunlabeled
Extended Poisson-Log-Logistic Distribution
Jehan. A. Almamy Almamy
2019· article· en· International Journal of Statistics and Probability· Decision Sciences
distilled prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Statistical Inference
William W. Hsieh
2023· book-chapter· en· Cambridge University Press eBooks· Decision Sciences
distilled prediction:candidate · metaepi_narrowconsensus · none
3
citations
afffundunlabeled
Assessing global change when data are sparse
Marc A. Maes, Markus R. Dann
2011· article· en· International Journal of Risk Assessment and Management· Decision Sciences
distilled prediction:candidate · noneconsensus · none
3
citations
afffundunlabeled
Scale Counting
Stefan H. Steiner, Robert J. MacKay
2004· article· en· Technometrics· Decision Sciences
distilled prediction:candidate · noneconsensus · none
3
citations
afffundunlabeled
Nearest Neighbor Multivariate Time Series Forecasting
Huiliang Zhang, Ping Nie, Lijun Sun, Benoît Boulet
2024· article· en· IEEE Transactions on Neural Networks and Learning Systems· Decision Sciences
distilled prediction:candidate · scholarly_communicationconsensus · none
3
citations
affno abstractunlabeled
Evaluation and Ranking of Market Forecasters
David H. Bailey, Jonathan M. Borwein, Amir Salehipour, Marcos López de Prado
2017· article· en· SSRN Electronic Journal· Decision Sciences
distilled prediction:candidate · noneconsensus · none
3
citations
affunlabeled
On Logistic and Generalized Logistic Distributions
Ritu Gupta, K. Jayakumar, Thomas Mathew
2004· article· en· Calcutta Statistical Association Bulletin· Decision Sciences
distilled prediction:candidate · metaresearch+insufficient_payloadconsensus · insufficient_payload
3
citations
affaboutunlabeled
expe?rimentation statistique et les probabilite?s
Maurice Halbwachs
2002· book· fr· classiques des sciences sociales· Decision Sciences
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+insufficient_payloadconsensus · sts
2
citations
affno abstractunlabeled
Introduction: The Economics of Industrial Production
Ruud Teunter, Krisztina Demeter, Stefan Minner, Pamela Ritchie
2014· article· en· International Journal of Production Economics· Decision Sciences
distilled prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About