Treating peripheral vestibular disease‐associated nausea
Bibliographic record
Abstract
Evaluation of diagnostic anesthesia during equine lameness examination requires comparison of complex movement patterns and can be influenced by expectation bias. There is limited research about how changes in movement asymmetries after successful analgesia are affected by different exercise conditions. Movement asymmetry of head, withers and pelvis was quantified in N = 31 horses undergoing forelimb or hindlimb diagnostic anesthesia. Evaluation on a straight line and a circle was performed with subjective diagnostic anesthesia outcome and quantitative changes recorded. Mixed linear models ( P < .05) analyzed the differences in movement asymmetry before/after diagnostic anesthesia -random factor: horse, fixed factors: surface (soft, hard), direction (straight, inside, outside, inside-outside average), diagnostic anesthesia outcome (negative, partially positive, positive) and two-way interactions. Forelimb diagnostic anesthesia influenced primary movement asymmetry (all head and withers parameters) and compensatory movement asymmetry (two pelvic parameters) either individually ( P .009) or in interaction with surface ( P .03). Hindlimb diagnostic anesthesia influenced primary movement asymmetry (all pelvic parameters) and compensatory movement asymmetry (two head and two withers parameters) either individually ( P .04) or in interaction with surface ( P .01;) or direction ( P .006). Direction was also significant individually for two pelvic parameters ( P .04). Changes in primary movement asymmetries after partially positive or positive outcomes indicated improvement in the blocked limb. Compensatory changes were mostly in agreement with the 'law of sides'. The changes were more pronounced on the hard surface for hindlimb lameness and on the soft surface for forelimb lameness. Withers asymmetry showed distinct patterns for forelimb and hindlimb lameness potentially aiding clinical decision-making.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".