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
IEEE Transactions on Signal Processing
Topic
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.

391 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.
391 works in the cohort · of 4,299,418page 2 of 8

Labels cover 0 of 391 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 391 of 391 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.

afffundunlabeled
A Multisensor Multi-Bernoulli Filter
Augustin-Alexandru Saucan, Mark Coates, Michael Rabbat
2017· article· en· IEEE Transactions on Signal Processing· Computer Science
machine prediction:candidate · noneconsensus · none
96
citations
affunlabeled
On Spatial Aliasing in Microphone Arrays
Jacek Dmochowski, Jacob Benesty, Sofiène Affes
2008· article· en· IEEE Transactions on Signal Processing· Computer Science
machine prediction:candidate · noneconsensus · none
89
citations
fundno affunlabeled
Multi-User Regularized Zero-Forcing Beamforming
Long D. Nguyen, Hoang Duong Tuan, Trung Q. Duong, H. Vincent Poor
2019· article· en· IEEE Transactions on Signal Processing· Engineering
machine prediction:candidate · noneconsensus · none
72
citations
affunlabeled
A Multiple-Detection Probability Hypothesis Density Filter
Xu Tang, Xin Chen, Michael McDonald, Ronald Mahler, Ratnasingham Tharmarasa, Thiagalingam Kirubarajan
2015· article· en· IEEE Transactions on Signal Processing· Computer Science
machine prediction:candidate · noneconsensus · none
67
citations
affunlabeled
A Fast Robust Recursive Least-Squares Algorithm
Leonardo Rey Vega, Hernán G. Rey, Jacob Benesty, S. Tressens
2008· article· en· IEEE Transactions on Signal Processing· Engineering
machine prediction:candidate · noneconsensus · none
58
citations
affunlabeled
Generalized S transform
Michael D. Adams, F. Kossentini, Rabab Ward
2002· article· en· IEEE Transactions on Signal Processing· Computer Science
machine prediction:candidate · noneconsensus · none
55
citations

How this was built: Screen · Findings · About