Bilateral thoracic radiographs increase lesion detection in horses with pneumonia or pulmonary neoplasia but do not bring any additional benefit for inflammatory or diffuse pulmonary disease
Bibliographic record
Abstract
Published studies describing the effects of bilateral radiographic projections on the detection of equine pulmonary lesions are currently lacking. The objectives of this retrospective, single center, observational study were to compare unilateral and bilateral thoracic radiographic projections for the detection of pulmonary lesions in a group of horses. Based on their clinical diagnosis, 167 adults and foals with bilateral thoracic radiographs were classified as having pneumonia (n = 88), inflammatory or diffuse pulmonary disease (n = 72), and pulmonary masses (n = 7). After an initial interrater repeatability test, right-to-left and left-to-right projections were anonymized and independently interpreted by a radiologist blinded to the clinical diagnosis. Scores were attributed for each pattern/lesion (alveolar, interstitial, bronchial, nodules/masses, cavitary lesions) and each quadrant. Agreement between scores from each projection was evaluated with Bland-Altman plots. Lesions identified on one side but not on the contralateral projection were considered discordant. There was no preferential lateralization of pulmonary lesions. The prevalence of discordance was 14.4%, 9.0%, and 4.2% for alveolar pattern, nodules/masses, and cavitary lesions, respectively. Up to nine horses (10.2%) with pneumonia could have been misdiagnosed. A pulmonary mass would have been missed in one case. For inflammatory or diffuse disease, discordance was slight, and the addition of contralateral projections had no impact on radiographic interpretation. In conclusion, in horses with pneumonia or neoplasia, bilateral projections, or adding at least one contralateral caudoventral view, increased the probability of identifying pulmonary lesions. In horses with inflammatory or diffuse disease, bilateral thoracic radiography provided no additional benefit.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".