Mapping the development of white matter tracts with diffusion tensor imaging
Bibliographic record
Abstract
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 studentt‐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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".