Ultrasonographic detection of early atrophy of the intrinsic laryngeal muscles of horses
Bibliographic record
Abstract
OBJECTIVE: To describe the ultrasonographic changes in the cricoarytenoideus dorsalis (CAD) and cricoarytenoideus lateralis (CAL) muscles of horses before and at various times during the 32 weeks after unilateral neurectomy of the right recurrent laryngeal nerve. ANIMALS: 28 healthy Standardbreds. PROCEDURES: For each horse, the appearance of the CAD and CAL muscles on the right (neurectomized) and left (control) sides was serially monitored ultrasonographically by percutaneous (CAD and CAL) and transesophageal (CAD) approaches. The ultrasonographic images were assessed to determine the mean pixel intensity, muscle thickness, and appearance grade, and comparisons were made between the muscles of the neurectomized and control sides. RESULTS: The muscle appearance grade and mean pixel intensity for the CAL and CAD muscles on the neurectomized side were significantly increased by 2 and 4 weeks, respectively, after the neurectomy. The transesophageal approach enhanced the ultrasonographic visibility of the CAD muscle and allowed us to detect a significant decrease in the thickness of the CAD muscle on the neurectomized side over time, compared with thickness of the CAD muscle on the control side. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested ultrasonography can be used to successfully assess the CAL and CAD muscles of horses. A qualitative grading scheme was sufficient for successful detection and monitoring of muscle atrophy and reduced the need for image standardization. The transesophageal approach described for assessment of the CAD muscle warrants further investigation.
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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 | 0.000 | 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".