MétaCan
Menu
Back to cohort
Record W2016628198 · doi:10.1111/1467-7687.00369

Mapping the development of white matter tracts with diffusion tensor imaging

2002· article· en· W2016628198 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDevelopmental Science · 2002
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsDiffusion MRICorpus callosumWhite matterFractional anisotropyPsychologyGyrusNeuroscienceAudiologyMedicineMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

Abstract In this study, the development of white matter was studied using an optimized diffusion tensor imaging (DTI) protocol in 20 normal subjects (10–40 years old). The normal development of white matter tracts was addressed by comparing the diffusion anisotropy results between two sub‐groups: eight adults (26–38 years old) and eight adolescents (13–15 years old). The difference in myelination extent between these two groups as indexed by the fractional anisotropy was identified by conducting a student t ‐test of the measured diffusion anisotropy maps. Significant differences ( p < 0.01) were detected in the gyrus frontalis medialis (GFM), gyrus temporalis medialis (GTM) and gyrus cinguli (GC), in addition to the developmental changes in corpus callosum. A brief overview of previous published DTI studies in developmental science and current progress in DTI techniques is also given at the end of this paper. It may be useful for readers interested in using DTI to study developmental problems but who are not familiar with the various technical aspects.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.167
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.292
Teacher spread0.226 · 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