Bibliographic record
Abstract
This review is designed to evaluate and interpret studies relevant to the locomotory mode known as brachiation, particularly as performed by the Hylobatid apes: the gibbon and siamang species. The older literature and its conclusions are evaluated against recent work performed by the author and other research groups working on brachiation models, either computer simulations or physical robots. The gibbon displays two types of brachiation: continuous contact, analogous to walking, and ricochetal, analogous to running. Both brachiation gaits display substantial pendular exchange between kinetic and potential energy. However, the fundamental feature of either of these gaits is the minimization of collisional energy loss. Collisional energy loss due to discontinuities in the trajectory of the center of mass is emerging as key in understanding locomotion using limbs in any terrestrial environment. The insight gained from this perspective applied to gibbon locomotion demonstrates that this is a critical factor in understanding many of the maneuvers employed by these animals, and can provide novel new interpretations of the morphological specializations that characterize the group. It is observed that these animals could brachiate using either totally active (muscle powered) or totally passive (nonmuscular) mechanisms. The active option would be metabolically costly, but provides substantial motion plasticity, while the passive option has the potential for profound economy, but does not allow a means to effectively contend with the inconsistencies present in the animal's natural environment. The conclusion is that the body form of brachiators and the locomotion behaviors they exhibit are a compromise between these two extremes, and these features of the gibbon's biology can only be understood by recognizing the role of collisional energy loss and evaluating both passive and active motion options together.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".