Bedside ultrasonography performed by family physicians in outpatient medical offices in Whitehorse, Yukon.
Bibliographic record
Abstract
INTRODUCTION: We sought to determine the current practices and opinions of family physicians in Whitehorse, YT, regarding bedside ultrasonography performed by family physicians in outpatient medical offices. METHODS: A paper survey was administered to Whitehorse family physicians. Only those who had worked for longer than 6 months in a community outpatient clinic in Whitehorse were invited to participate. RESULTS: The response rate of our survey was 44%. None of the respondents reported currently using bedside ultrasonography in their outpatient medical offices; however, 78% reported having training in ultrasonography and using it in another setting. Of the respondents, 94% stated they would consider using bedside ultrasonography in their outpatient medical office. Economics was the biggest reported barrier in the use of bedside ultrasonography in outpatient medical offices. CONCLUSION: A wealth of experience in bedside ultrasonography already exists among family physicians in Whitehorse, and an overwhelming majority of physicians are ready to embrace its use in outpatient offices. However, the skills and willingness of family physicians have not translated into the use of bedside ultrasonography in outpatient medical offices.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".