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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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Diverse Music Education Insights
Retraction
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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.

1,227 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.
1,227 works in the cohort · of 4,299,418page 25 of 25

Labels cover 0 of 1,227 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 1,227 of 1,227 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.

affvenueaboutunlabeled
The Discerning Process of Song Selection
Kim Friesen Wiens
2022· article· en· Alberta Academic Review· Arts and Humanities
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Outstanding Dissertation Award
2023· article· en· Bulletin of the Council for Research in Music Education· Arts and Humanities
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
fundno affunlabeled
Toward Neurotechnology for Musical Creativity
Эдуардо Миранда
2023· book-chapter· en· The MIT Press eBooks· Arts and Humanities
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Are 11 Weeks Weak? A Conversation With Instructors
Gagan Sarkaria, Toni M. Schuster
2011· article· en· Contemporary Issues in Education Research (CIER)· Arts and Humanities
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Musical Ways of Knowing
Christine McMillan
2005· article· International journal of education and the arts· Arts and Humanities
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Where Does This Accent Come From?
Aslı Duru
2024· article· en· ACME· Arts and Humanities
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Remembrances for John Lachs (1934–2023)
Herman J. Saatkamp, Deron Boyles, Phil Oliver
2025· article· en· The Pluralist· Arts and Humanities
machine prediction:candidate · noneconsensus · none
0
citations
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