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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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Spreadsheets and End-User Computing
Retraction
Abstract
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Label status

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
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

127 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
127 works in the cohort · of 4,299,418page 3 of 3

Labels cover 0 of 127 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 127 of 127 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
Session details: End-user programming I
Carl Gutwin
2010· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Appendix: Working in Excel
Tara Ivanochko
2021· other· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Educational ISSUES IN business schools
Thomas A. Grossman, Stephen G. Powell
2001· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Closure
Ezra Hauer
2014· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
HOT: Hadamard-based Optimized Training
Seonggon Kim, Juncheol Shin, Seung-taek Woo, Eunhyeok Park
2025· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
SPECIAL SESSION: Inspired to Excel!
Irmajean Bajnok
2017· article· en· 44th Biennial Convention (28 October - 01 November 2017)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
The value of spreadsheet programs to planners
Mitchell Alan William Kenyon
2010· article· en· cIRcle (University of British Columbia)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Excel tips
Raj Raj, David Orozco-Baldovinos, Davide Rapotez
2020· preprint· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Introduction to Special Issue SAP 2018
Bernhard E. Riecke, Joseph Kearny
2018· article· en· ACM Transactions on Applied Perception· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Bothynotus pilosus Boheman 1852
2014· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Trend 1991 - 2007. Statistics Canada. CANSIM: Education, Training and Learning - Adult Education and Training | Country: Canada | Province: Saskatchewan | Table: Registered apprenticeship training, registrations by major trade groups and sex | Variable: Building construction trades, Both sexes | Units: #, 1991-2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-067.
2015· other· en· Data Planet· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Beginning Again
2016· other· DigitalCommons - WayneState (Wayne State University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1145/3772318.3808946
AI Generated
2000· article· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1145/3772318.3808951
AI Generated
2000· article· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
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