Short communication: Ultrasonographic assessment of the thorax as a fast technique to assess pulmonary lesions in dairy calves with bovine respiratory disease
Bibliographic record
Abstract
The aim of this study was to assess inter- and intraoperator agreement when assessing lung consolidation secondary to bovine respiratory disease (BRD) by thoracic ultrasonography. Ten calves were blindly assessed by 3 operators with varying expertise in thoracic ultrasound to look for lung consolidation and the presence of comet-tail artifacts (COMT). Systematic ultrasonography of the thorax was performed using an 18-site per side assessment with a linear 8.5-MHz probe. The status of the calves [healthy (n=4) vs. treated for BRD (n=6)] was not known by the operators. The interoperator kappa agreement for detecting consolidation was moderate to almost perfect (from 0.6 to 1.0) depending on the operator's experience (diagnosis of consolidation if depth ≥1cm). The intraclass correlation coefficient for consistency was 0.71 for a single measurement and 0.88 for average measurement. The intraclass correlation coefficient for agreement was 0.73 for single measurements and 0.89 for average measurements. These values were considered good for single measurements and excellent for average measurements. Systematic ultrasonography of the thorax can be used routinely to assess lung consolidation in dairy calves and can therefore be of importance, especially for assessment of subclinical BRD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".