Obstetric and Gynecologic Resident Ultrasound Education Project
Bibliographic record
Abstract
OBJECTIVES: Ultrasound is a critical diagnostic imaging tool in obstetrics and gynecology (Ob/Gyn). Obstetric ultrasound is taught during residency, but we suspected a gap in Gyn ultrasound education. Proficiency in Gyn ultrasound allows real-time interpretation and management of pelvic disease and facilitates technical skill development for trainees learning blinded procedures. This study sought to evaluate ultrasound education in Canada's Ob/Gyn residency programs and assess whether residents and physicians perceived a need for a formalized Gyn ultrasound curriculum. METHODS: We distributed a needs assessment survey to residents enrolled in Canadian Ob/Gyn residency programs and to all obstetrician/gynecologists registered as members of the Society of Obstetricians and Gynaecologists of Canada. Residents were asked to specify their current training in ultrasound and to rate the adequacy of their curriculum. All respondents rated the importance of proficiency in pelvic ultrasound for practicing obstetrician/gynecologists as well as the perceived need for formalized ultrasound training in Ob/Gyn residency programs. RESULTS: Eighty-two residents and 233 physicians completed the survey. Extents and types of ultrasound training varied across residency programs. Most residents reported inadequate exposure to Gyn ultrasound, and most residents and physicians agreed that it is important for obstetrician/gynecologists to be proficient in Gyn ultrasound and that the development of a standardized Gyn ultrasound curriculum for residency programs is important. CONCLUSIONS: Current ultrasound education in Ob/Gyn varies across Canadian residency programs. Training in Gyn ultrasound is lacking, and both trainees and physicians confirmed the need for a standardized Gyn ultrasound curriculum for residency programs in Canada.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".