Linear Discriminant Analysis for Investigating Differences in Upper Body Movement Symmetry in Horses before/after Diagnostic Analgesia in Relation to Expert Judgement
Bibliographic record
Abstract
Diagnostic analgesia and lunging are parts of the equine lameness examination, aiding veterinarians in localizing the anatomical region(s) causing pain-related movement deficits. Expectation bias of visual assessment and complex movement asymmetry changes in lame horses on the lunge highlight the need to investigate data-driven approaches for optimally integrating quantitative gait data into veterinary decision-making to remove bias. A retrospective analysis was conducted with inertial sensor movement symmetry data before/after diagnostic analgesia relative to subjective judgement of efficacy of diagnostic analgesia in 53 horses. Horses were trotted on the straight and on the lunge. Linear discriminant analysis (LDA) applied to ten movement asymmetry features quantified the accuracy of classifying negative, partial and complete responses to diagnostic analgesia and investigated the influence of movement direction and surface type on the quality of the data-driven separation between diagnostic analgesia categories. The contribution of movement asymmetry features to decision-making was also studied. Leave-one-out classification accuracy varied considerably (38.3-57.4% for forelimb and 36.1-56.1% for hindlimb diagnostic analgesia). The highest inter-category distances (best separation) were found with the blocked limb on the inside of the circle, on hard ground for forelimb diagnostic analgesia and on soft ground for hindlimb diagnostic analgesia. These exercises deserve special attention when consulting quantitative gait data in lame horses. Head and pelvic upward movement and withers minimum differences were the features with the highest weighting within the first canonical LDA function across exercises and forelimb and hindlimb diagnostic analgesia. This highlights that movement changes after diagnostic analgesia affect the whole upper body. Classification accuracies based on quantitative movement asymmetry changes indicate considerable overlap between subjective diagnostic analgesia categories.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".