Quantitative DTI Assessment in Human Lumbar Stabilization Muscles at 3 T
Bibliographic record
Abstract
OBJECTIVES: To characterize diffusion tensor imaging (DTI) tensor eigenvalues (λ1, λ2, λ3), fractional anisotropy, mean diffusivity, and radial diffusivity in healthy lumbar musculature. METHODS: Seventeen healthy subjects (10 men, 7 women; mean age, 28 ± 7 years) were scanned using a 3.0-T magnetic resonance imaging. Axial DTI was performed using 15 diffusion directions (b = 400 mm/s) at the L4 level. Oswestry Low Back Pain and Godin Physical Activity questionnaires were administered to rule out underlying lower back problems. RESULTS: Skeletal muscle DTI metrics were similar to those previously published. All measurements showed low coefficients of variation, except for quadratus lumborum. Laterality was not significant. Significant sex differences were observed in the quadratus lumborum (P < 0.05). Significant correlations were found between subjects' weight and body mass index with fractional anisotropy and λ1 of the multifidus muscles. CONCLUSIONS: The DTI metrics in paraspinal muscles can be reliably measured and are influenced by body mass index and weight but not by age or physical activity.
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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 | 0.002 |
| 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 | 0.000 |
| 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".