Reply to: In response: “The core competencies in hospital medicine: Procedures 2025 update”
Bibliographic record
Abstract
We thank Olson et al. for their thoughtful comments about the challenges and reasons that graduate medical education (GME) training programs face in providing trainees with the opportunities necessary to develop their procedural competency skills. 1 The professional responsibilities and types of procedures hospitalists may be expected to perform can vary significantly across institutions and practice settings.As part of their commitment to lifelong learning, hospitalists bear the professional responsibility for evaluating and maintaining their knowledge and skills, which may at times include acquiring new skills to develop competency in areas relevant to their practice, including the performance of procedures. 2 The Core Competencies document provides all hospitalists and trainees with a framework of measurable learning objectives on topics relevant to hospital medicine; however, it does not define an absolute set of topics to be used by GME training programs, nor does it establish boundaries for hospital medicine practice. 3 agree that to more effectively allocate limited resources, GME programs may consider tailoring procedural training to align with trainees' intended future practice. 4Other proposed innovative solutions to increase procedural competency among hospitalists and trainees include creating medical procedure services and collaborating with other GME programs and specialists.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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 teacher head, 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".