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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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Multi-Agent Systems and Negotiation
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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.

940 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.
940 works in the cohort · of 4,299,418page 2 of 19

Labels cover 0 of 940 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 940 of 940 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.

affno abstractunlabeled
Towards decision support for participatory democracy
David Rı́os Insua, Gregory E. Kersten, Jesús Ríos, Carlos Grima
2007· article· en· Information Systems and e-Business Management· Computer Science
machine prediction:candidate · noneconsensus · none
51
citations
affunlabeled
Triggering verbal presuppositions
Márta Abrusán
2010· article· en· Proceedings from Semantics and Linguistic Theory· Computer Science
machine prediction:candidate · noneconsensus · none
46
citations
affunlabeled
Justification of Argumentation Schemes
Douglas Walton
2005· article· en· The Australasian Journal of Logic· Computer Science
machine prediction:candidate · noneconsensus · none
45
citations
affunlabeled
Goal-based Reasoning for Argumentation
Douglas Walton
2015· book· en· Cambridge University Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
45
citations
affvenueunlabeled
The Basic Slippery Slope Argument
Douglas Walton
2015· article· en· Informal Logic· Computer Science
machine prediction:candidate · noneconsensus · none
43
citations
affunlabeled
Intelligent agents, simulation, and gaming
Levent Yılmaz, Tuncer Ören, Nasser-Ghasem Aghaee
2006· article· en· Simulation & Gaming· Computer Science
machine prediction:candidate · noneconsensus · none
42
citations
affunlabeled
Adaptive Collaboration Based on the E-CARGO Model
Haibin Zhu, Ming Hou, MengChu Zhou
2012· article· en· International Journal of Agent Technologies and Systems· Computer Science
machine prediction:candidate · noneconsensus · none
36
citations
affunlabeled
Types of Dialogue and Burdens of Proof
Douglas Walton
2010· book-chapter· en· Frontiers in artificial intelligence and applications· Computer Science
machine prediction:candidate · noneconsensus · none
36
citations
fundno affunlabeled
Intelligent Agents for Online Learning
Choonhapong Thaiupathump, John R. Bourne, Olin Campbell
2019· article· en· Online Learning· Computer Science
machine prediction:candidate · noneconsensus · none
36
citations
affno abstractunlabeled
A distributed multi-agent meeting scheduler
Elhadi Shakshuki, Hsiang-Hwa Koo, Darcy Benoit, Daniel Silver
2007· article· en· Journal of Computer and System Sciences· Computer Science
machine prediction:candidate · noneconsensus · none
35
citations

How this was built: Screen · Findings · About