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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.

2,427 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.
2,427 works in the cohort · of 4,299,418page 31 of 49

Labels cover 37 of 2,427 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 2,427 of 2,427 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
Back Cover Image
Shaun Adams, Rainer Grün, David McGahan, Jian‐xin Zhao, Yuexing Feng, Ai Duc Nguyen +5 more
2019· paratext· en· Geoarchaeology· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Safdie
2013· article· en· Iowa State University Digital Repository (Iowa State University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
2014_SR_data.tab
Saulo Castro, Arturo Sánchez‐Azofeifa
2020· dataset· en· Harvard Dataverse· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Editor's desktop
Irene L. Travis
2014· article· en· Bulletin of the Association for Information Science and Technology· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Is C&RL Ready for a Data Sharing Policy?
Minglu Wang, Adrian K. Ho, Kristen Totleben
2023· article· en· University of Chicago· Computer Science
machine prediction:candidate · metaresearch+open_scienceconsensus · metaresearch
0
citations
affunlabeled
Is C&RL Ready for a Data Sharing Policy?
Minglu Wang, Adrian K. Ho, Kristen Totleben
2023· article· en· Open MIND· Computer Science
machine prediction:candidate · metaresearch+open_scienceconsensus · metaresearch
0
citations
aboutno affunlabeled
Economics Unit
2008· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
humus.io | working paper
2019· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · metaresearch+insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About