MétaCan
Menu
Back to cohort
Record W2178472169 · doi:10.1016/j.dib.2015.10.044

Trajectories of cortical surface area and cortical volume maturation in normal brain development

2015· article· en· W2178472169 on OpenAlexafffund
Simon Ducharme, Matthew D. Albaugh, Tuong‐Vi Nguyen, James J. Hudziak, J.M. Mateos-Pérez, Aurélie Labbe, Alan C. Evans, Sherif Karama

Bibliographic record

VenueData in Brief · 2015
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMcGill University Health CentreMontreal Neurological Institute and HospitalDouglas Mental Health University InstituteMcGill University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Institutes of HealthNational Institute of Child Health and Human DevelopmentCanadian Institutes of Health ResearchFondation de l'Hôpital Général de MontréalFondation Brain Canada
KeywordsBrain developmentNeuroscienceBrain sizeVolume (thermodynamics)Cerebral cortexBiologyAnatomyMedicinePhysicsMagnetic resonance imaging

Abstract

fetched live from OpenAlex

This is a report of developmental trajectories of cortical surface area and cortical volume in the NIH MRI Study of Normal Brain Development. The quality-controlled sample included 384 individual typically-developing subjects with repeated scanning (1-3 per subject, total scans n=753) from 4.9 to 22.3 years of age. The best-fit model (cubic, quadratic, or first-order linear) was identified at each vertex using mixed-effects models, with statistical correction for multiple comparisons using random field theory. Analyses were performed with and without controlling for total brain volume. These data are provided for reference and comparison with other databases. Further discussion and interpretation on cortical developmental trajectories can be found in the associated Ducharme et al.׳s article "Trajectories of cortical thickness maturation in normal brain development - the importance of quality control procedures" (Ducharme et al., 2015) [1].

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.002
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: Dataset · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.100
GPT teacher head0.295
Teacher spread0.195 · 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
GenreDataset

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

Citations52
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueData in BriefSame topicFunctional Brain Connectivity StudiesFrench-language works237,207