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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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NeuroImage
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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.

1,942 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.
1,942 works in the cohort · of 4,299,418page 3 of 39

Labels cover 1 of 1,942 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 1,942 of 1,942 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.

fundno affunlabeled
Generative models of the human connectome
Richard F. Betzel, Andrea Avena‐Koenigsberger, Joaquín Goñi, Ye He, Marcel A. de Reus, Alessandra Griffa +8 more
2015· article· en· NeuroImage· Neuroscience
machine prediction:candidate · noneconsensus · none
343
citations
afffundno abstractunlabeled
Neurofeedback with fMRI: A critical systematic review
Robert T. Thibault, Amanda MacPherson, Michael Lifshitz, Raquel R. Roth, Amir Raz
2017· review· en· NeuroImage· Neuroscience
machine prediction:candidate · noneconsensus · none
339
citations
affunlabeled
The current state-of-the-art of spinal cord imaging: Methods
Patrick W. Stroman, Claudia A. M. Gandini Wheeler‐Kingshott, Mark Bacon, Jan M. Schwab, Rachael L. Bosma, J.C. Brooks +16 more
2013· review· en· NeuroImage· Medicine
machine prediction:candidate · noneconsensus · none
332
citations
fundno affunlabeled
Bayesian segmentation of brainstem structures in MRI
Juan Eugenio Iglesias, Koen Van Leemput, Priyanka Bhatt, Christen Casillas, Shubir Dutt, Norbert Schuff +3 more
2015· article· en· NeuroImage· Computer Science
machine prediction:candidate · noneconsensus · none
292
citations

How this was built: Screen · Findings · About