Comparison of Computed Tomography and Routine Radiography of the Tympanic Bullae in the Diagnosis of Otitis Media in the Calf
Bibliographic record
Abstract
BACKGROUND: Otitis media is difficult to diagnose antemortem. Case reports have described computed tomography (CT) in the diagnosis, but not all cases were confirmed. HYPOTHESIS: CT is a sensitive and specific imaging modality of the tympanic bullae and can be used as the gold standard for the diagnosis of otitis media. ANIMALS: Sixteen Holstein calves 5-7 weeks of age were included. METHODS: Prospective study. All calves were sedated with i.v. xylazine (0.05-0.15 mg/kg) for routine radiography (3 views) and CT of the tympanic bullae followed by necropsy. RESULTS: Based upon necropsy findings, 10 of 16 calves were affected with otitis media, 4 unilaterally and 6 bilaterally. Imaging changes associated with otitis media included increased soft tissue opacity within the bulla, thickening of the bulla wall, enlarged bulla, and osteolysis of the bulla wall and trabeculations. The most frequent radiographic changes were lysis of trabeculations and increased soft tissue opacity, which were present in 56.3% of affected bullae. On CT, increased soft tissue opacity within the bulla was present in 93.8% of affected bullae. Sensitivity of radiography and CT was 68.8 and 93.8% and specificity was 50 and 100%, respectively. The κ value between radiography and CT with necropsy diagnosis was 0.19 for radiography, indicating poor agreement, and 0.94 for CT, indicating excellent agreement. CONCLUSION: CT is more specific, more sensitive, and easier to interpret than radiography and can be used as the gold standard in the diagnosis of otitis media in the calf.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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 | 0.001 |
| 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 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".