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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.

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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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Forecasting Techniques and Applications
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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.

affaffiliation
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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.

497 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.
497 works in the cohort · of 4,299,418page 2 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. 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
Significance Testing Needs a Taxonomy
M. T. Bradley, Andrew Brand
2016· article· en· Psychological Reports· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
19
citations
venueno affunlabeled
Improvement of Regression Forecasting Models
Vasiliy Aleksandrovich Zubakin, О. А. Косоруков, Nikita Moiseev
2015· article· en· Modern Applied Science· Decision Sciences
machine prediction:candidate · noneconsensus · none
16
citations
affaboutunlabeled
Bombardier Aftermarket Demand Forecast with Machine Learning
Pierre Dodin, Jingyi Xiao, Yossiri Adulyasak, Neda Etebari Alamdari, Léa Gauthier, Philippe Grangier +2 more
2023· article· en· INFORMS Journal on Applied Analytics· Decision Sciences
machine prediction:candidate · noneconsensus · none
16
citations
afffundunlabeled
Constructing a group distribution from individual distributions.
Denis Cousineau, Jean‐Philippe Thivierge, Bradley Harding, Yves Lacouture
2015· article· en· Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale· Decision Sciences
machine prediction:candidate · noneconsensus · none
14
citations
affaboutunlabeled
Forecasting Supply Chain Demand Using Machine Learning Algorithms
Réal A. Carbonneau, Rustam Vahidov, Kevin Laframboise
2009· book-chapter· en· Advances in intelligent information technologies series/Advances in intelligent information technologies (AIIT) book series· Decision Sciences
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
What is a Good Calibration Question?
Victoria Hemming, Anca M. Hanea, Mark A. Burgman
2021· article· en· Risk Analysis· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
13
citations
affunlabeled
Hybrid forecasting of geopolitical events<sup>†</sup>
D. M. Benjamin, Fred Morstatter, Ali E. Abbas, Andrés Abeliuk, Pavel Atanasov, Stephen Bennett +23 more
2023· article· en· AI Magazine· Decision Sciences
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
The Anatomy of Out-of-Sample Forecasting Accuracy
Daniel Borup, Philippe Goulet Coulombe, David E. Rapach, Erik Christian Montes Schütte, Sander Schwenk-Nebbe
2022· article· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations
aboutno affunlabeled
DYNAMIC QUANTILE MODELS
Joann Jasiak, Christian Gouriéroux
2006· preprint· en· RePEc: Research Papers in Economics· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations
affno abstractunlabeled
Econometrics: A Bird's Eye View
John Geweke, Joël L. Horowitz, M. Hashem Pesaran
2006· article· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
10
citations
afffundno abstractunlabeled
Non-Standard Errors
Albert J. Menkveld, Anna Dreber, Felix Holzmeister, Jürgen Huber, Michael Kirchler, Michael Razen +330 more
2021· article· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
10
citations
afffundunlabeled
Single-step simple ROC curve fitting via PCA.
John R. Vokey
2016· article· en· Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale· Decision Sciences
machine prediction:candidate · noneconsensus · none
10
citations
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