Length changes in the human masseter muscle after jaw movement
Bibliographic record
Abstract
The human masseter is a multilayered, complex muscle contributing to jaw motion. Because variations in stretch may cause muscle fibers to function over different portions of their length-tension curves, the aim of this study was to determine how parts of the masseter lengthen or shorten during voluntary jaw movements made by living subjects. Magnetic resonance (MR) imaging and optically-based jaw-tracking were used to measure muscle-insertion positions for four parts of the muscle with six degrees of freedom (DOF), before and after maximum-opening, jaw protrusion and laterotrusion in four adult males. Muscle part lengths and intramuscular tendon lengths were calculated, and these data, with fiber-tendon ratios published previously, were used to estimate putative changes in fiber-length. During maximum jaw-opening, the largest increases in muscle length (34-83%) occurred in the medial part of the deep masseter, whereas the smallest changes occurred in the posterior-most, superficial masseter (2-19%). Smaller changes were found during movement to the ipsilateral side, than during protrusion and movement to the contralateral side. On maximum opening, putative fibers in the deep masseter lengthened up to 83%, whereas those of the superficial masseter stretched up to 72%. The masseter muscle does not stretch uniformly for major jaw movement. Jaw motion to the ipsilateral side causes little length change in any part, and the effect of tendon-stretch on estimated fiber lengths is not substantial. The stretch that occurs infers there are task-related changes in the active and passive tensions produced by different muscle regions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".