Inertial properties of the German Shepherd Dog
Bibliographic record
Abstract
One of the most popular dog breeds deployed by both the police and military has been the German Shepherd yet little is known about the morphology or body segment parameters of this breed. Such measures are essential for developing biomechanical models which, in turn, may guide clinicians in developing surgical interventions, injury treatment and prevention procedures. This paper provides a complete set of body segment parameters and inertial properties for the German Shepherd. Morphometric measures and 3-dimensional inertial properties, including mass, centre of mass, moment of inertia and volume, were measured from 17 segments from 6 German Shepherd police service dog cadavers. Using whole body mass and geometric modelling, 11 regression equations were developed for predicting segment masses, and 33 equations were developed for predicting moments of inertia. Using these data, inverse dynamic analyses may be applied in future investigations of canine mechanics, guiding surgical procedures, rehabilitation and training especially for the German Shepherd breed but potentially for other breeds too.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".