Work loop dynamics of the pigeon (<i>Columba livia</i>) humerotriceps demonstrate potentially diverse roles for active wing morphing
Bibliographic record
Abstract
Control of wing shape is believed to be a key feature that allows most birds to produce aerodynamically efficient flight behaviours and high maneuverability. Anatomical organization of intrinsic wing muscles suggests specific roles for the different motor elements in wing shape modulation, but testing these hypothesized functions requires challenging measurements of muscle activation and strain patterns, and force dynamics. The wing muscles that have been best characterized during flight are the elbow muscles of the pigeon (Columba livia). In vivo studies during different flight modes revealed variation in strain profile, activation timing and duration, and contractile cycle frequency of the humerotriceps, suggesting that this muscle may alter wing shape in diverse ways. To examine the multifunction potential of the humerotriceps, we developed an in situ work loop approach to measure how activation duration and contractile cycle frequency affected muscle work and power across the full range of activation onset times. The humerotriceps produced predominantly net negative power, likely due to relatively long stimulus durations, indicating that it absorbs work, but the work loop shapes also suggest varying degrees of elastic energy storage and release. The humerotriceps consistently exhibited positive and negative instantaneous power within a single contractile cycle, across all treatments. When combined with previous in vivo studies, our results indicate that both within and across contractile cycles, the humerotriceps can dynamically shift among roles of actuator, brake, and stiff or compliant spring, based on activation properties that vary with flight mode.
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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 | 0.000 | 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".