The use of veterinary point-of-care ultrasound by veterinarians: A nationwide Canadian survey.
Bibliographic record
Abstract
This survey assessed how veterinary point-of-care ultrasound (VPOCUS), including abdominal and thoracic focused assessment with sonography for trauma (AFAST, TFAST), is used across Canada. Seventy-four veterinarians completed an online survey; 88% (65/74) used ultrasound, 94% (61/65) performed AFAST, and 69% (45/65) performed TFAST. Reasons for not performing VPOCUS included no machine/poor quality machine, lack of experience/confidence, and lack of training/education. Abdominal effusion, and pleural and pericardial effusion were the most frequently diagnosed AFAST and TFAST pathologies, respectively. Lung and cardiovascular ultrasound examinations were infrequently performed. Subpleural consolidation was rarely included in VPOCUS. Most respondents performed VPOCUS, with AFAST being more frequently and confidently preformed than TFAST. More training, education, and standardization of techniques appear to be key elements to help build confidence and experience, particularly with regard to TFAST applications and diagnosis.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".