MétaCan
ENFR
Menu
Cohort builder

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.

Export CSVExport JSONAPI query

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.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Topic
Music and Audio Processing
Retraction
Abstract
Evidence source
Study design
Label agreement
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.

1,031 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
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 5 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. 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
Searching in audio
Abhishek Ranjan, Ravin Balakrishnan, Mark Chignell
2006· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
15
citations
afffundunlabeled
Overtone focusing in biphonic tuvan throat singing
Christopher Bergevin, Chandan Narayan, Joy Williams, Natasha Mhatre, Jennifer K. E. Steeves, Joshua G. W. Bernstein +1 more
2020· article· en· eLife· Computer Science
machine prediction:candidate · noneconsensus · none
15
citations
aboutno affunlabeled
Instrument Library (MUMS) Revised
Tuomas Eerola, Rafael Ferrer
2008· article· en· Music Perception An Interdisciplinary Journal· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
14
citations
affunlabeled
Predicting Genre Labels For Artist Using Freedb.
James Bergstra, Alexandre Lacoste, Douglas Eck
2006· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Speech recognition with quaternion neural networks
Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid, Georges Linarès, Renato De Mori
2018· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
A meta-analysis of acoustic correlates of timbre dimensions
Stephen McAdams, Bruno L. Giordano, Patrick Susini, Geoffroy Peeters, Vincent Rioux
2006· article· en· The Journal of the Acoustical Society of America· Computer Science
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Finding Emotional-Laden Resources on the World Wide Web
Kathrin Knautz, Diane Rasmussen Pennington, Stefanie Schmidt, Tobias Siebenlist, Wolfgang G. Stock
2011· article· en· Information· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
An e-Research approach to Web-scale music analysis
David De Roure, Kevin Page, Benjamin Fields, Tim Crawford, J. Stephen Downie, Ichiro Fujinaga
2011· article· en· Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Robotaba Guitar Tablature Transcription Framework.
Gregory Burlet, Ichiro Fujinaga
2013· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
11
citations
affunlabeled
MIDI Passage Retrieval Using Cell Phone Pictures of Sheet Music
Daniel Yang, Thitaree Tanprasert, Teerapat Jenrungrot, Mengyi Shan, Timothy Tsai
2019· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
11
citations
affunlabeled
Music Browsing Using A Tabletop Display.
Stephen Hitchner, Jennifer Murdoch, George Tzanetakis
2007· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
11
citations
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
machine prediction:candidate · noneconsensus · none
11
citations
← previousnext →

How this was built: Screen · Findings · About