Age‐Related Differences in the Quantitative Echo Texture of the Median Nerve
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.
Bibliographic record
Abstract
OBJECTIVES: Currently, there are no quantitative data on the echo texture of a peripheral nerve. This study was designed to objectively compare the differences in the echo texture of the median nerve in the young and the elderly. METHODS: The median nerves of 10 healthy young volunteers (<30 years old; group Y) and 10 elderly patients undergoing lower limb surgery (>60 years old; group E) were scanned at the mid forearm by a standardized protocol. The echo texture of a normalized median nerve image was analyzed for the echo intensity and spatial distribution of pixels. Noise in the image was reduced by using a median filter, and thresholding was performed thereafter. In the resultant binary image, the cross-sectional area, echo intensity, white area index, and black area index of the median nerve were determined by computerized texture analysis. RESULTS: The mean cross-sectional area of the median nerve in group E was significantly smaller than that in group Y (P = .002). The mean echo intensity and white area index in group E were significantly higher than those in group Y (P= .002 and .012). The mean black area index in group E was correspondingly significantly lower than that in group Y (P = .012). In group Y, the mean white area index was significantly lower than the black area index (P = .006) but not in group E (P = .213). CONCLUSIONS: There are significant differences in the echo texture of the median nerve between the young and the elderly. These differences may be due to age-related changes in the relative proportion of neural fascicles and connective tissue within the nerve.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it