Nephrology Fellowship Clinician-Performed Ultrasound Curriculum
Bibliographic record
Abstract
Fluid overload (FO) contributes significantly to the development of cardiovascular disease among patients with end-stage kidney disease (ESKD) on hemodialysis (HD), yet remains underappreciated due to limitations of the physical exam [1]. Lung ultrasound (US) is an established tool for quantification of FO [2]. Previous validation of quantitative lung US among nephrology attendings using a remote web-based lung ultrasound training has been demonstrated [3]. Interest in ultrasound education among nephrology fellows is high [4]. Clinician-performed ultrasound curricula for nephrology fellows have been described previously, however fellows’ competency in quantitative lung US has not been described [5]. In the present study we aimed to assess the current level of knowledge among nephrology fellows as well as the efficacy of a brief training course in quantitative lung US.
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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 | 0.001 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".