Bite force and jaw biomechanics in the subterranean rodent Talas tuco-tuco (<i>Ctenomys talarum</i>) (Caviomorpha: Octodontoidea)
Bibliographic record
Abstract
The Talas tuco-tuco ( Ctenomys talarum Thomas, 1898) is a South American subterranean rodent that digs using both forelimbs and incisors, the latter being used when animals face hard soils and fibrous roots. In this rodent, the incisors are also used during intermale competition for mates. Bite forces were measured on wild females (n = 21) and males (n = 21) (both adult and young individuals) using a force transducer. Bite force was significantly higher in adult males than in females (32 vs. 27 N, respectively). Bite forces calculated on the physiological cross-section of jaw adductor muscles in dissected specimens were slightly higher than in vivo measurements. Regressions against body mass showed that bite force scaled with positive allometry, with slopes of 0.89 (females) and 0.99 (males). No significant differences were observed, neither in the slope nor in the y intercept of both sexes’ equations; therefore intersexual differences in bite forces observed in adults should mainly be due to size dimorphism. Considering that soil hardness of C. talarum’s typical habitat averages 100 N/cm2, and taking into account incisor’s cross-section, it was assessed that the pressure exerted by jaw adductor muscles at the incisors level is three times higher than that required for soil penetration.
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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".