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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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ICT Impact and Policies
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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.

1,506 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.
1,506 works in the cohort · of 4,299,418page 19 of 31

Labels cover 5 of 1,506 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 1,506 of 1,506 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
Index
J.F. Hayes, Thimma V. J. Ganesh Babu
2004· paratext· en· Engineering
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Regulation and Policy Reforms
Sylvie Albert, Don Flournoy, Rolland LeBrasseur
2010· book-chapter· en· IGI Global eBooks· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Discount Coupons in Rural Markets
2019· article· en· Journal of Applied Business and Economics· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Conclusion
Sylvie Albert, Don Flournoy, Rolland LeBrasseur
2011· book-chapter· en· IGI Global eBooks· Engineering
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
e-Infrastructure and e-Services
Max Agueh, Fatna Belqasmi, Marco Zennaro, Roch Glitho
2016· book· en· Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1541-9800(09)70149-8
2000· article· en· Time to knit· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
The Network Society
Gilbert Germain
2005· article· en· Canadian Journal of Political Science· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Lessons from Canada
Geneviève A. Bonina
2017· article· en· MedienJournal· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
What Skills do IT Companies Look for in New Developers?
João Eduardo Montandon, Cristiano Politowiski, Luciana Lourdes Silva, Marco Túlio Valente, Fábio Petrillo, Yann‐Gaël Guéhéneuc
2019· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Editors’ Note
2022· article· en· Journal of Popular Music Studies· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Benefits Beyond Revenue
George Watt, Howard Abrams
2018· book-chapter· en· Apress eBooks· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Big Winners and Small Losers of Zero-rating
Niloofar Bayat, T. B. Richard, Vishal Misra, Dan Rubenstein
2022· article· en· ACM Transactions on Modeling and Performance Evaluation of Computing Systems· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
New Media Codes and Assumptions
Elliot Gaines
2012· book-chapter· en· Semiotics· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Literacy Issues in the Era of the New Media
José Afonso Furtado
2021· article· en· IASL Annual Conference Proceedings· Engineering
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About