Positions of pivot points in quadrupedal locomotion: limbs and trunk global control in four different dog breeds
Bibliographic record
Abstract
Abstract Dogs ( Canis familiaris ) prefer the walk at lower speeds and the more economical trot at speeds ranging from 0.5 Fr up to 3 Fr. Important works were carried out to understand these gaits at the levels of center of mass, joint mechanics, and muscular control. However, less is known about the global control goals for limbs and overall locomotion, and of whether these global control goals are gait or breed specific. For walk and trot, we analyzed dog global dynamics based on motion capture and single leg kinetic data recorded from treadmill locomotion of French Bulldog (N = 4), Whippet (N = 5), Malinois (N = 4) and Beagle (N = 5). Dogs displayed two virtual pivot points (VPP) during walk and trot each. One resembles control of both thoracic (fore) limbs and is roughly located above and caudally to the scapular pivot, while the second is located roughly above and cranially to the hip and mirrors the control of the pelvic (hind-) limbs. The positions of VPPs and the patterns of the legs‘ axial and tangential functions were gait and breed related. However, breed related changes were mainly exposed by the French Bulldog. The position of VPPs relative to the proximal pivots explains the propulsive and breaking forces observed in quadrupedal locomotion and may help to reduce limb work. In combination with former work, from the present study the VPP template emerges as the expression of a simple and general global control rule for both bipeds and quadrupeds.
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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".