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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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Auction Theory 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
fundfunder
venuejournal
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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.

1,300 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.
1,300 works in the cohort · of 4,299,418page 20 of 26

Labels cover 1 of 1,300 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 1,300 of 1,300 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
Noisy Signaling in Monopoly
Leonard J. Mirman, Egas M. Salgueiro, Marc Santugini
2013· preprint· en· RePEc: Research Papers in Economics· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Predatory Bidding in Sequential Auctions
Hikmet Günay, Xin Meng
2007· article· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Security and Trust of Online Auction Systems in E-Commerce
Pouwan Lei, Lih-Jiun Lo, C.R. Chatwin, Robert C. Young, Malcolm I. Heywood, A. Nur Zincir‐Heywood
2003· book-chapter· en· IGI Global eBooks· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
afffundunlabeled
(Bad) reputation in relational contracting
Rahul Deb, Matthew Mitchell, Mallesh M. Pai
2022· preprint· en· Theoretical Economics· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Honesty and Informal Agreements
Martin Dufwenberg, Maroš Servátka, Radovan Vadovič
2015· preprint· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
afffundunlabeled
Multi-item Auctions for Automatic Negotiation
Houssein Ben-Ameur, Brahim Chaib-draa, Peter Kropf
2002· preprint· en· RePEc: Research Papers in Economics· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
An Open Access Market for Global Communications
Peter Cramton, Erik Bohlin, Simon Brandkamp, Jason Dark, Darrell Hoy, Albert S. Kyle +3 more
2024· preprint· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · scholarly_communicationconsensus · none
1
citations
affunlabeled
Data and AI Markets in a Nutshell
Jian Pei, Xiaohui Yu
2025· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Gains to bidder firms revisited
B. Espen Eckbo, Karin S. Thorburn
2012· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Under ε-Best Response
2011· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
PRINCIPAL AuTHOR
2012· article· en· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Rules Versus Mechanisms
Joshua S. Gans
2023· book-chapter· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
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