MétaCan
ENFR
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.

Export CSVExport JSONAPI query

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
Applied Stochastic Models in Business and Industry
Topic
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.

104 results · 1 filter active ·
Results by year
20022025
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.
104 works in the cohort · of 4,299,418page 2 of 3

Labels cover 0 of 104 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 104 of 104 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Authors' Rejoinder
N. Balakrishnan, Debasis Kundu
2019· article· en· Applied Stochastic Models in Business and Industry· Mathematics
distilled prediction:candidate · noneconsensus · none
3
citations
aboutno affunlabeled
Modeling swine population dynamics at a finer temporal resolution
Luca Sartore, Yi‐Jun Wei, Emilola Abayomi, Seth Riggins, Gavin Corral, Valbona Bejleri +1 more
2020· article· en· Applied Stochastic Models in Business and Industry· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
A semi‐Markov model of disease recurrence in insured dogs
Xikui Wang, Jeffrey Pai, Kevin J. Shand
2007· article· en· Applied Stochastic Models in Business and Industry· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
1
citations
afffundunlabeled
A Bayesian two‐armed bandit model
Xikui Wang, You Liang, Lysa Porth
2018· article· en· Applied Stochastic Models in Business and Industry· Decision Sciences
distilled prediction:candidate · metaepi_narrowconsensus · none
1
citations
afffundunlabeled
Real option valuation of timber harvesting contracts
Hemantha S. B. Herath, John S. Jahera
2021· article· en· Applied Stochastic Models in Business and Industry· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
1
citations
affunlabeled
A journey of discovery with George Box
D. W. Bacon
2014· article· en· Applied Stochastic Models in Business and Industry· Decision Sciences
distilled prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Malliavin calculus in a binomial framework
Samuel N. Cohen, Robert J. Elliott, Tak Kuen Siu
2018· article· en· Applied Stochastic Models in Business and Industry· Economics, Econometrics and Finance
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
An intensity‐based approach for equity modeling
Marcos Escobar, Tim Friederich, Mikhail Krayzler, Luis Seco, Rudi Zagst
2011· article· en· Applied Stochastic Models in Business and Industry· Economics, Econometrics and Finance
distilled prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About