Modeling Temperature Effects On Transient Mechanical Responses In Muscle
Bibliographic record
Abstract
We have simulated the effects of temperature on transient mechanical responses in muscle using a model of crossbridge micro-mechanics. The incorporation of temperature dependence was achieved by taking into account that certain parameters, such as the maximum shortening velocity (V,), rate of actomyosin ATPase and tetanic tension (To) are temperature dependent. The resulting simulations are consistent with experimental data. ATPase and V, are strongly correlated, we have assumed that the energy liberation rate scales with V, in such a way that the relation between energy liberation rate and velocity preserves its form if it is normalized with respect to V,. In developing our model for crossbridge micro-mechanics, the functional-dependence of f and g on crossbridge angular velocity d, was determined from the relation between energy liberation rate and velocity. Since this relation is simply scaled by V, it follows that f and g will also be scaled by V,. One of the fundamental equations used in our model is the equation for power balance [I].
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".