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Normative morphometric data for cerebral cortical areas over the lifetime of the adult human brain

2017· article· en· W2614054318 on OpenAlexafffund
Olivier Potvin, Louis Dieumegarde, Simon Duchesne

Bibliographic record

VenueNeuroImage · 2017
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversité Laval
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthOffice of Naval ResearchNational Institute on AgingFonds de Recherche du Québec - SantéMcDonnell Center for Systems NeuroscienceLundbeckfondenAmerican Hearing Research FoundationDiabetes Research Center, University of WashingtonAlzheimer's Drug Discovery FoundationNational Institutes of HealthServierFujirebio EuropeStavros Niarchos FoundationU.S. Department of DefenseCommonwealth Scientific and Industrial Research OrganisationCanada Foundation for InnovationAlzheimer SocietyGenentechAlvin J. Siteman Cancer CenterNational Institute of Diabetes and Digestive and Kidney DiseasesTourette Association of AmericaTakeda Pharmaceutical CompanyNational Multiple Sclerosis SocietyNovartis Pharmaceuticals CorporationCanadian Institutes of Health ResearchFoundation for Barnes-Jewish HospitalGE HealthcareAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsLeon Levy FoundationNational Institute on Deafness and Other Communication DisordersF. Hoffmann-La RocheChild Mind InstituteBioClinicaBiogenPfizerAbbVieBiogen IdecMerckEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentGlaxoSmithKlineRocheAvid RadiopharmaceuticalsBrain Research FoundationDana FoundationNew York State Office of Mental HealthAlzheimer's AssociationBurroughs Wellcome FundSimons FoundationEli Lilly and CompanyBristol-Myers SquibbNational Center for Research ResourcesJohn Douglas French Alzheimer's FoundationMichael J. Fox Foundation for Parkinson's ResearchNational Science Foundation
KeywordsNormativeMagnetic resonance imagingScannerStandard deviationPsychologyVariance (accounting)SegmentationStatisticsHuman brainNuclear medicineMedicineMathematicsRadiologyNeuroscienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.089
GPT teacher head0.332
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations85
Published2017
Admission routes2
Has abstractno

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