LOWER LIMB MUSCLE ASSESSMENT USING DIFFUSION TENSOR AND BLOOD OXYGEN-LEVEL DEPENDENT IMAGING
Bibliographic record
Abstract
Diffusion tensor (DT) and blood oxygen-level dependent (BOLD) imaging are two noninvasive magnetic resonance (MR) techniques that have been used to probe skeletal muscle microstructure and microvasculature, respectively. Over a series of four studies, the work in this thesis aimed at furthering our understanding of baseline DT metrics and BOLD signals in lower limb muscles (calf and foot) of healthy young subjects. Since postural changes have been shown to alter numerous quantities, including fluid volumes and muscle cross sectional area, DT indices and BOLD signal characteristics were examined in response to movement from upright to supine position. Reductions of 3.2-6.7% and 3.4-7.5% were measured in calf DT eigenvalues and apparent diffusion coefficient (ADC) in the various muscles, following 34 and 64 minutes of supine rest, respectively (P Establishment of baseline diffusion metrics in the foot region was feasible (chapter 6). Examination of foot DT indices in response to positional change showed that the metrics decreased from 2.7-4.6% following 34 minutes of supine rest (P
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".