Does the Medical College Admission Test Predict Clinical Reasoning Skills? A Longitudinal Study Employing the Medical Council of Canada Clinical Reasoning Examination
Bibliographic record
Abstract
BACKGROUND: To investigate the predictive validity of the Medical College Admission Test (MCAT) for clinical reasoning skills upon completion of medical school. METHOD: A total of 597 students (295 males, 49.4%; 302 females, 50.6%) participated from 1991 to 1999. Stepwise multiple regressions of the MCAT and premedical school GPA (independent variables) on the Part 1(declarative knowledge) and Part 2 (clinical reasoning) of the Medical Council of Canada Examinations (dependent variables) were employed. RESULTS: For Part 1, the multiple regression revealed that three predictors (verbal reasoning, biological sciences, GPA) accounted for 23.3% of the variance, and for Part 2, two predictors (verbal reasoning, GPA) accounted for 11.2%. CONCLUSION: There is both convergent and divergent evidence for the predictive validity of the MCAT for clinical reasoning.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".