Expert-Type Knowledge Structure in Medical Students is Associated With Increased Odds of Diagnostic Success
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The relation between knowledge structure and diagnostic performance is unclear. Similarly, variables affecting knowledge structure are poorly understood. PURPOSE: The 1st objective was to examine the relation between concepts in knowledge structure and diagnostic performance. The 2nd objective was to examine the relation between the use of diagnostic schemes by small-group preceptors and knowledge structure of medical students. METHODS: This was a cross-sectional study of 1st-year medical students in 4 clinical presentations: hyponatremia, hyperkalemia, metabolic acidosis, and metabolic alkalosis. The 1st dependent variable was diagnostic success with the number of expert-type concepts in knowledge structure (determined by concept sorting), diagnostic scheme use by preceptors, and clinical presentation as independent variables. The 2nd dependent variable was the number of expert-type concepts in knowledge structure with diagnostic scheme use by preceptors and clinical presentation as independent variables. Data were analyzed using multiple logistic and linear regression. RESULTS: Thirty 1st-year medical students participated. After adjusting for clinical presentation and scheme use by preceptors, the number of expert-type concepts in knowledge structure was associated with increased odds of diagnostic success (odds ratio 1.18 [1.03, 1.35], p = .016). After adjustment for clinical presentation, scheme use by preceptors was associated with increased number of expert-type concepts in knowledge structure (2.22 vs. 1.86, p = .01, d = 0.23). CONCLUSIONS: The number of expert-type concepts in knowledge structure is associated with increased odds of diagnostic success. Scheme use by small-group preceptors is associated with an increased number of expert-type concepts in knowledge structure.
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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 | 0.008 | 0.325 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it