MétaCan
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.

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
Speech 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.

1,408 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.
1,408 works in the cohort · of 4,299,418page 23 of 29

Labels cover 2 of 1,408 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 1,408 of 1,408 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
Reduction of airflow noise in telephone handsets
Michael R. Stinson, Gilles A. Daigle, John F. Quaroni
2004· article· en· The Journal of the Acoustical Society of America· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Speech resynthesis from 1/f<b> <i>β</i> </b> noise
Robert Fuhrman, Eric Vatikiotis‐Bateson
2016· article· en· The Journal of the Acoustical Society of America· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Noise Suppression in Cellular Telephony
Malay Gupta, Chris Forrester, Sean Simmons
2009· article· en· Canadian acoustics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Toward better automatic speech recognition
Douglas O’Shaughnessy, W. Wang, Wen Zhu, Vincent Barreaud, T. Nagarajan, R. Muralishankar
2005· article· en· Canadian acoustics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Signal processing for a visual hearing aid
Ellen McDonald, Hans Kunov, Willy Wong
2001· article· en· Canadian acoustics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Frequency Filtering
Peter Zizler, Roberta La Haye
2024· book-chapter· en· Compact textbooks in mathematics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Robust automatic recognition of telephone speech
Douglas O’Shaughnessy, Selouani Sid‐Ahmed
2003· article· en· The Journal of the Acoustical Society of America· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About