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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.

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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EEG and Brain-Computer Interfaces
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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.

3,062 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.
3,062 works in the cohort · of 4,299,418page 59 of 62

Labels cover 7 of 3,062 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 3,062 of 3,062 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.

affno abstractunlabeled
Retinal Flicker Stimulation Affects the Cardiac Rhythm
P. Sauvageau, C. Boisjoly, Julie Morin, V. Diaconu
2007· article· en· Investigative Ophthalmology & Visual Science· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Correction: Requirement Analysis for Data-Driven Electroencephalography Seizure Monitoring Software to Enhance Quality and Decision Making in Digital Care Pathways for Epilepsy: A Feasibility Study from the Perspectives of Health Care Professionals
Pantea Keikhosrokiani, Johanna Annunen, Jonna Komulainen‐Ebrahim, Jukka Kortelainen, Mika Kallio, Päivi Vieira +2 more
2025· article· en· JMIR Human Factors· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
PERFORM Dataset; one control subject
PERFORM Centre
2019· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
P.113 Down Syndrome: robust neurophysiological perspectives
Jonathan Norton, Roland N. Auer, Salah Almubarak
2018· article· en· Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
GP.5 Entropy on routine EEG: an interictal marker of seizure frequency?
Émile Lemoine, Julien Tessier, G McDuff, Manon Robert, Dènahin Hinnoutondji Toffa, Frédéric Lesage +2 more
2021· article· en· Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Analysis of Brain Excitability After Transcranial Direct Current Stimulation and Brain-Computer Interface Based on Motor Imagery on a Post-stroke Patient
Leticia Silva, Jessica Paola Souza Lima, Sheila Schreider, Denis Delisle-Rodríguez, Sridhar Krishnan, Teodiano Bastos-Filho
2024· book-chapter· en· World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Automatic early detection of cognitive decline
Neta B. Maimon, Lior Molcho, Tomer Loterrman, Narkiss Pressburger, Ady Sasson, Nathan Intrator
2020· article· en· Alzheimer s & Dementia· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About