Obstetric-Focused POCUS Training for Medical Students
Bibliographic record
Abstract
Point of care ultrasound (POCUS) is rapidly expanding throughout the United States. Due to its ability to quickly and accurately diagnose and guide therapy for critical conditions, POCUS is becoming routine in many specialties, with established guidelines in fields such as emergency medicine and critical care 1, 2, 3. For example, a study entitled "Ultrasound Integration in Undergraduate Medical Education: Comparison of Ultrasound Proficiency Between Trained and Untrained Medical Students" initiated an Emergency Medicine POCUS curriculum for first-year medical students that showed an increase in ultrasound capability 4. In short, as POCUS becomes more common practice, medical schools are beginning to implement POCUS training into their undergraduate medical education; studies from these institutions demonstrate that implementing a formal ultrasound curriculum into preclinical medical education significantly increases medical students' POCUS capabilities4, 5 and assisted in their understanding and learning of anatomy 6, 7.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.009 |
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".