Canine trachealis muscle shortening and cartilage mechanics
Bibliographic record
Abstract
Canine trachealis muscle will shorten by 70% of resting length when maximally stimulated in vitro. In contrast, trachealis muscle will shorten by only 30-40% when stimulated in vivo. To examine the possibility that an elastic load applied by the tracheal cartilage contributes to the in vivo limitation of shortening, single pairs of sonomicrometry crystals were inserted into the trachealis muscle at the level of the fifth cartilage ring in five dogs. The segment containing the crystals was then excised and mounted on a tension-testing apparatus. Points on the active length-tension curve and the passive length-tension relation of the cartilage only were determined. The preload applied to the muscle before contraction varied from 10 to 40 g (mean 21 +/- 4 g). The afterload applied by the cartilage during trachealis contraction ranged from 13 to 56 g (30 +/- 6 g). The calculated elastic afterloads were substantial and appeared to be sufficient to explain the degree of shortening observed in four of the seven rings; in the remaining three rings, the limitation of shortening was greater than would be expected from the elastic load provided by the cartilage. Additional sources of loading and/or additional mechanisms may contribute to limited in situ shortening. In summary, tracheal cartilage applies a preload and an elastic afterload to the trachealis that are substantial and contribute to the limitation of trachealis muscle shortening in vivo.
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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 | 0.001 | 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".