Morphometry ofMacaca mulatta forelimb. I. Shoulder and elbow muscles and segment inertial parameters
Bibliographic record
Abstract
The present study examined the morphometric properties of the forelimb, including the inertial properties of the body segments and the morphometric parameters of 21 muscles spanning the shoulder and/or elbow joints of six Macaca mulatta and three M. fascicularis. Five muscle parameters are presented: optimal fascicle length (L(0)(M)), tendon slack length (L(S)(T)), physiological cross-sectional area (PCSA), pennation angle (alpha(0)), and muscle mass (m). Linear regressions indicate that muscle mass, and to a lesser extent PCSA, correlated with total body weight. Segment mass, center-of-mass, and the moment of inertia of the upper arm, forearm, and hand are also presented. Our data indicate that for some segments, radius of gyration (rho) predicts segment moment of inertia better than linear regressions based on total body weight. Key differences between the monkey and human forelimb are highlighted.
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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 | 0.000 | 0.000 |
| 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".