Evaluation of a novel accelerometer for kinetic gait analysis in dogs.
Bibliographic record
Abstract
The objective of this study was to evaluate a novel accelerometer-based sensor system, the Walkabout Portable Gait Monitor (WPGM), for use in kinetic gait analysis of dogs. The accelerometer was compared to the common reference standard of force platform analysis. Fifteen client-owned, orthopedically sound dogs of various breeds underwent simultaneous force platform and accelerometer gait trials to measure peak vertical forces (PVFs). The agreement between PVF for the accelerometer and force platform was measured using concordance correlation coefficient (CCC) and was found, overall, to be moderate [CCC = 0.51; 95% confidence interval (CI): 0.46 to 0.56]. The agreement between PVF for the accelerometer and force platform for the forelimbs was positive and substantial (CCC = 0.79; 95% CI: 0.74 to 0.84) and for the hind limbs was positive and low (CCC = 0.34; 95% CI: 0.29 to 0.38). As measured by the accelerometer, PVF was systematically higher than as measured by the force platform (forelimbs 55.3 N, hind limbs 144.3 N). It was also found that, when positioned over the lumbar spine, the WPGM cannot measure PVF of the individual forelimbs and hind limbs, which limits its use as a clinical tool to measure kinetic variables in dogs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".