Relationship Between Performance on the NBME<sup>®</sup>Comprehensive Clinical Science Self-Assessment and USMLE<sup>®</sup>Step 2 Clinical Knowledge for USMGs and IMGs
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 Comprehensive Clinical Science Self-Assessment (CCSSA) is a web-administered multiple-choice examination that includes content that is typically covered during the core clinical clerkships in medical school. Because the content of CCSSA items resembles the content of the items on Step 2 Clinical Knowledge (CK), CCSSA is intended to be a tool for students to help assess whether they are prepared for Step 2 CK and to become familiar with its content, format, and pacing. PURPOSES: This study examined the relationship between performance on the National Board of Medical Examiners® CCSSA and performance on the United States Medical Licensing Examination® Step 2 CK for U.S./Canadian (USMGs) and international medical school students/graduates (IMGs). METHODS: The study included 9,789 participants who took CCSSA prior to their first Step 2 CK attempt. Linear and logistic regression analyses investigated the relationship between CCSSA performance and performance on Step 2 CK for both USMGs and IMGs. RESULTS: CCSSA scores explained 58% of the variation in first Step 2 CK scores for USMGs and 60% of the variation for IMGs; the relationship was somewhat different for the two groups as indicated by statistically different intercepts and slopes for the regression lines based on each group. Logistic regression results showed that examinees in both groups with low scores on CCSSA were at a higher risk of failing their first Step 2 CK attempt. CONCLUSIONS: RESULTS suggest that CCSSA can provide students with a valuable practice tool and a realistic self-assessment of their readiness to take Step 2 CK.
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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 | 0.025 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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