Temporal-spatial gait analysis by use of a portable walkway system in healthy Labrador Retrievers at a walk
Bibliographic record
Abstract
OBJECTIVE: To establish a protocol to collect temporal-spatial gait analysis variables by use of a portable walkway system in Labrador Retrievers at a walk and to determine reference values. ANIMALS: 56 healthy Labrador Retrievers. PROCEDURES: 6 passes across the walkway (3 passes in each direction) were recorded. Inclusion criteria for a pass were that the dog was at a walk (velocity, 60.0 to 90.0 cm/s) and had minimal head turning. The first 3 passes that met the inclusion criteria were analyzed for each dog. RESULTS: Mean stride length was 88.4 cm. Mean stance time (ST) of forelimbs and hind limbs was 0.62 and 0.56 seconds, respectively. Mean stance time percentage (ST%; proportion of stance time to total gait cycle time) for forelimbs and hind limbs was 55.6% and 50.2%, respectively. Mean total pressure index (TPI) of forelimbs and hind limbs was 27.1 and 17.4, respectively. Mean number of sensors (NS) activated by each paw strike of forelimbs and hind limbs was 17 and 13, respectively. Mean forelimb-to-hind limb symmetry ratios were 1.11 (ST), 1.10 (ST%), 1.62 (TPI), and 1.37 (NS). Symmetry ratios for left limbs to right limbs, left forelimb to right forelimb, and left hind limb to right hind limb were 1.00. CONCLUSIONS AND CLINICAL RELEVANCE: A protocol for collection of temporal-spatial gait analysis variables with a portable walkway system in Labrador Retrievers at a walk was developed, and reference values for variables and symmetry ratios were reported. Further research will determine the extent to which symmetry ratios differ in dogs with orthopedic disorders.
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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 | 0.001 | 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".