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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.

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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INFORMS Journal on Applied Analytics
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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.

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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.

83 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.
83 works in the cohort · of 4,299,418page 1 of 2

Labels cover 0 of 83 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 83 of 83 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
A Florida County Locates Disaster Recovery Centers
Jamie Dekle, Mariel S. Lavieri, Erica L. Martin, H. Emir-Farinas, Richard L. Francis
2005· article· en· INFORMS Journal on Applied Analytics· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
91
citations
afffundunlabeled
Optimization Helps Shermag Gain Competitive Edge
Mustapha Ouhimmou, Sophie D’Amours, Robert Beauregard, Daoud Aı̈t-Kadi, Satyaveer S. Chauhan
2009· article· en· INFORMS Journal on Applied Analytics· Engineering
machine prediction:candidate · noneconsensus · none
19
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
affaboutunlabeled
Preferred Scenarios in the Sport of Curling
Keith A. Willoughby, Kent J. Kostuk
2004· article· en· INFORMS Journal on Applied Analytics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
15
citations
affaboutunlabeled
Automated Pathologist Scheduling at The Ottawa Hospital
Jonathan Patrick, Amine Montazeri, Wojtek Michalowski, Diponkar Banerjee
2019· article· en· INFORMS Journal on Applied Analytics· Health Professions
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
A Decision Support System for Attended Home Services
Bruno P. Bruck, Filippo Castegini, Jean‐François Cordeau, Manuel Iori, Tommaso Poncemi, Dario Vezzali
2020· article· en· INFORMS Journal on Applied Analytics· Engineering
machine prediction:candidate · noneconsensus · none
11
citations

How this was built: Screen · Findings · About