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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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Anesthesia and Neurotoxicity Research
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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.

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.

729 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.
729 works in the cohort · of 4,299,418page 6 of 15

Labels cover 1 of 729 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 729 of 729 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.

aboutno affunlabeled
Brain Waste: The Neglect of Animal Brains
Bruno Cozzi, Luca Bonfanti, Elisabetta Canali, Michela Minero
2020· article· en· Frontiers in Neuroanatomy· Neuroscience
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Outcomes Research in Vulnerable Pediatric Populations
Ka-Eun M. Lee, Thomas G. Diacovo, Johanna Calderon, Mary Byrne, Caleb Ing
2018· review· en· Journal of Neurosurgical Anesthesiology· Neuroscience
machine prediction:candidate · noneconsensus · none
8
citations
aboutno affunlabeled
Neuroscientific Foundations of Anesthesiology
George A. Mashour, Ralph Lydic
2012· article· en· European Journal of Anaesthesiology· Neuroscience
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Developmental Neurotoxicity: An Update
Philipp Houck, Ansgar M. Brambrink, Jennifer Waspe, James D. O’Leary, Riva Ko
2018· article· en· Journal of Neurosurgical Anesthesiology· Neuroscience
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
What Next After GAS and PANDA?
Caleb Ing, Virginia Rauh, David O. Warner, Lena S. Sun
2016· article· en· Journal of Neurosurgical Anesthesiology· Neuroscience
machine prediction:candidate · noneconsensus · none
7
citations
fundno affunlabeled
Neural Mechanisms of Anesthesia
2003· book· en· Humana Press eBooks· Neuroscience
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Cerebral protection
Bruno Bissonnette
2004· review· en· Pediatric Anesthesia· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
venueno affunlabeled
Exploring the in vivo toxicity of nanoparticles
Laura Romero‐Castillo, Inmaculada Posadas, Valentı́n Ceña
2017· article· en· Canadian Journal of Chemistry· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
Anesthesia, surgery and neurodegeneration
Roderic G. Eckenhoff, Emmanuel Planel
2013· article· en· Progress in Neuro-Psychopharmacology and Biological Psychiatry· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations

How this was built: Screen · Findings · About