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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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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.

330 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.
330 works in the cohort · of 4,299,418page 4 of 7

Labels cover 0 of 330 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 330 of 330 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
Strong Optimal Classification Trees
Sina Aghaei, Andrés Gómez, Phebe Vayanos
2024· article· en· Operations Research· Computer Science
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Data Aggregation and Demand Prediction
Maxime C. Cohen, Renyu Zhang, Kevin Jiao
2022· article· en· Operations Research· Decision Sciences
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Quantity Premiums and Discounts in Dynamic Pricing
Yuri Levin, Mikhail Nediak, Андрей Бажанов
2014· article· en· Operations Research· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Dynamic Interday and Intraday Scheduling
Christos Zacharias, Nan Liu, Mehmet A. Begen
2022· article· en· Operations Research· Health Professions
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Optimal Subscription Planning for Digital Goods
Saeed Alaei, Ali Makhdoumi, Azarakhsh Malekian
2023· article· en· Operations Research· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
23
citations
affaboutunlabeled
Systemic Risk-Driven Portfolio Selection
Agostino Capponi, Alexey Rubtsov
2022· article· en· Operations Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
23
citations
affunlabeled
Competition in Service Industries
Gad Allon, Awi Federgruen
2007· article· en· Operations Research· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
22
citations
affunlabeled
Patient-Type Bayes-Adaptive Treatment Plans
M. Reza Skandari, Steven M. Shechter
2021· article· en· Operations Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
20
citations

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