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Record W4206614603 · doi:10.1017/cjn.2021.513

A Normative Brain MRI Database of Neurotypical Participants from 5 to 90 Years of Age

2022· article· en· W4206614603 on OpenAlexafffundvenue
Sarah Treit, Julia N. Rickard, Emily Stolz, Kevin Grant Solar, Peter Seres, Derek Emery, Christian Beaulieu

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2022
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of Alberta
FundersUniversity of AlbertaCanadian Institutes of Health ResearchWomen and Children's Health Research InstituteCanada Research ChairsChildren's Health Research Institute
KeywordsNeurotypicalNormativePsychologyMedicineDevelopmental psychologyPolitical scienceAutism

Abstract

fetched live from OpenAlex

Brain magnetic resonance imaging (MRI) studies of clinical populations often require comparison to a normative 'control' cohort, usually of similar age/sex, scanned with the same protocol. The goal here was to create a normative brain MRI database of common quantitative methods to be used in comparisons with a variety of neurological disorders across the lifespan. 378 neurotypical controls (aged 5-90 years; median 31 years; 216 females, 162 males) completed brain MRI, cognitive testing, clinical assessment, and a demographics questionnaire. In addition, this large normative sample will yield novel insight into healthy brain development and aging.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.086
GPT teacher head0.301
Teacher spread0.215 · 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

Citations6
Published2022
Admission routes3
Has abstractyes

Explore more

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