Bibliographic record
Abstract
The physiological cross‐sectional area (PCSA) of the mandibular adductor musculature in prosimian primates scales with positive allometry relative to body size. The chewing muscles of these primates are pinnate and fiber length scales with strong negative allometry relative to body size. Adductor mass scales with isometry relative to body size. Positive allometry of PCSA suggests that the muscles of larger prosimians are capable of producing greater force than would be predicted based on body size alone. However, this may reflect dietary differences between large‐bodied and small‐bodied species. Negative allometry of fiber length suggests that larger prosimians are more limited in their jaw gape. Isometry of chewing muscle mass is potentially an artifact of selection on PCSA and fiber length. In general, the anatomy of the chewing muscles in these prosimians conforms to previously reported patterns; however, some differences are apparent. Tarsiers show more muscular subdivision, especially in the temporalis, than do strepsirrhines. Differences in relative sizes of the individual chewing muscles likely reflect differences in diet and oral behavior. For example, in Propithecus the deep layers of the masseter are especially large. This may be related to its diet of tough objects, such as leaves. Data on PCSA, locations, and orientations of the muscles of mastication will contribute realistic parameters to models of masticatory biomechanics. Because PCSA is a proxy for the magnitude of force a muscle can produce, these data will contribute calibrations for electromyographic studies of the mandibular adductors. I thank Duke University, the University of Alberta, Sigma Xi, and the Natural Sciences and Engineering Research Council of Canada for funding.
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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) | 0.004 | 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".