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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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Music and Audio Processing
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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.

1,031 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.
1,031 works in the cohort · of 4,299,418page 6 of 21

Labels cover 2 of 1,031 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 1,031 of 1,031 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Can You Tell a Prodigy From a Professional Musician?
Gilles Comeau, Dominique T. Vuvan, Claudia Picard‐Deland, Isabelle Peretz
2017· article· en· Music Perception An Interdisciplinary Journal· Computer Science
distilled prediction:candidate · sts+scholarly_communication+insufficient_payloadconsensus · none
11
citations
afffundunlabeled
PulmoListener
Sejal Bhalla, Salaar Liaqat, Robert Wu, Andrea S. Gershon, Eyal de Lara, Alex Mariakakis
2023· article· en· Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies· Computer Science
distilled prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Music Genre Classification
Adam Lefaivre, John Z. Zhang
2018· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Loudness Assessment of Music and Speech
Esben Skovenborg, René Quesnel, Søren H. Nielsen
2004· article· en· Journal of the Audio Engineering Society· Computer Science
distilled prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Advances in Optimizing Recurrent Networks
Yoshua Bengio, Nicolas Boulanger-Lewandowski, Razvan Pascanu
2012· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
10
citations
affunlabeled
The SPECIAL System
Kevin Harrigan
2000· article· en· Journal of Research on Computing in Education· Computer Science
distilled prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Two Albanian Mosques: the acoustics discovery inside prayer rooms
Silvana Sukaj, Umberto Berardi, Giuseppe Ciaburro, Gino Iannace, Amelia Trematerra, Antonella Bevilacqua
2021· article· en· 2021 Immersive and 3D Audio: from Architecture to Automotive (I3DA)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
9
citations
affunlabeled
Decoding Music in the Human Brain Using EEG Data
Chris Foster, Dhanush Dharmaretnam, Haoyan Xu, Alona Fyshe, George Tzanetakis
2018· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
9
citations
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How this was built: Screen · Findings · About