Validation of an Ultrasound Imaging Technique of the Tympanic Bullae for the Diagnosis of Otitis Media in Calves
Bibliographic record
Abstract
BACKGROUND: Otitis media is a common disease in calves that can be subclinical, making antemortem on-farm diagnosis challenging. OBJECTIVES: To evaluate the sensitivity and specificity of ultrasonography of tympanic bullae for the diagnosis of clinical and subclinical otitis media and to evaluate the reproducibility of the technique. ANIMALS: Forty calves 19-50 days of age were selected from a veal calf farm. METHODS: Prospective study. Ultrasonography was first performed on the farm by ultrasonographer A (US A). Ultrasonography was repeated by ultrasonographer A (US A') and another ultrasonographer (US B) at the Centre Hospitalier Universitaire Vétérinaire. Images were later reread by both examiners and a diagnosis was recorded. The calves were euthanized and submitted for necropsy, and histopathologic diagnosis was used as the gold standard. RESULTS: Forty-five bullae were affected by otitis media and 35 bullae were normal. Sensitivity and specificity of the ultrasound technique ranged from 32 to 63% and 84 to 100%, respectively, depending on the examiner and classification of suspicious ultrasonography results. Kappa analysis to evaluate interobserver agreement between A' and B yielded a к value of 0.53. Agreement within the same examiner (A versus A') yielded a к value of 0.48, and real-time ultrasound versus rereading of recorded images for A' and B yielded к values of 0.58 and 0.75, respectively. CONCLUSIONS: Sensitivity and specificity of the ultrasound imaging technique are, respectively, low and high for diagnosis of clinical and subclinical otitis media in calves, with moderate reproducibility.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".