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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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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 2 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.

afffundno abstractunlabeled
Seizure prediction for therapeutic devices: A review
Kais Gadhoumi, Jean‐Marc Lina, Florian Mormann, Jean Gotman
2015· review· en· Journal of Neuroscience Methods· Neuroscience
machine prediction:candidate · noneconsensus · none
194
citations
afffundunlabeled
Prepared Movements Are Elicited Early by Startle
Anthony N. Carlsen, Romeo Chua, J. Timothy Inglis, David J. Sanderson, Ian M. Franks
2004· article· en· Journal of Motor Behavior· Neuroscience
machine prediction:candidate · noneconsensus · none
183
citations
fundno affunlabeled
Consciousness and complexity: a consilience of evidence
Simone Sarasso, Adenauer G. Casali, Silvia Casarotto, Mario Rosanova, Corrado Sinigaglia, Marcello Massimini
2021· article· en· Neuroscience of Consciousness· Neuroscience
machine prediction:candidate · noneconsensus · none
182
citations
affno abstractunlabeled
Sleep stage classification using single-channel EOG
Md. Mosheyur Rahman, Mohammed Imamul Hassan Bhuiyan, Ahnaf Rashik Hassan
2018· article· en· Computers in Biology and Medicine· Neuroscience
machine prediction:candidate · noneconsensus · none
176
citations
fundno affunlabeled
Obituary: Yukio Mano (1943–2004)
Katsunori Ikoma
2005· article· en· Journal of NeuroEngineering and Rehabilitation· Neuroscience
machine prediction:candidate · noneconsensus · none
173
citations
aboutno affunlabeled
A Residual Based Attention Model for EEG Based Sleep Staging
Wei Qu, Zhiyong Wang, Hong Hong, Zheru Chi, Dagan Feng, Ronald R. Grunstein +1 more
2020· article· en· IEEE Journal of Biomedical and Health Informatics· Neuroscience
machine prediction:candidate · noneconsensus · none
169
citations
affno abstractunlabeled
Can prepared responses be stored subcortically?
Anthony N. Carlsen, Romeo Chua, J. Timothy Inglis, David J. Sanderson, Ian M. Franks
2004· article· en· Experimental Brain Research· Neuroscience
machine prediction:candidate · noneconsensus · none
167
citations
afffundno abstractunlabeled
Learning to move machines with the mind
Andrea M. Green, John Kalaska
2010· review· en· Trends in Neurosciences· Neuroscience
machine prediction:candidate · noneconsensus · none
155
citations
affunlabeled
BCI meeting 2005-workshop on clinical issues and applications
Andrea Kübler, Vivian K. Mushahwar, Leigh R. Hochberg, John P. Donoghue
2006· article· en· IEEE Transactions on Neural Systems and Rehabilitation Engineering· Neuroscience
machine prediction:candidate · noneconsensus · none
154
citations
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