Script concordance testing: From theory to practice: AMEE Guide No. 75
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
The script concordance test (SCT) is used in health professions education to assess a specific facet of clinical reasoning competence: the ability to interpret medical information under conditions of uncertainty. Grounded in established theoretical models of knowledge organization and clinical reasoning, the SCT has three key design features: (1) respondents are faced with ill-defined clinical situations and must choose between several realistic options; (2) the response format reflects the way information is processed in challenging problem-solving situations; and (3) scoring takes into account the variability of responses of experts to clinical situations. SCT scores are meant to reflect how closely respondents' ability to interpret clinical data compares with that of experienced clinicians in a given knowledge domain. A substantial body of research supports the SCT's construct validity, reliability, and feasibility across a variety of health science disciplines, and across the spectrum of health professions education from pre-clinical training to continuing professional development. In practice, its performance as an assessment tool depends on careful item development and diligent panel selection. This guide, intended as a primer for the uninitiated in SCT, will cover the basic tenets, theoretical underpinnings, and construction principles governing script concordance testing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.678 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.013 |
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