Roadmap for a competency‐based educational curriculum in epileptology: report of the Epilepsy Education Task Force of the International League Against Epilepsy
Bibliographic record
Abstract
Teaching competency in the diagnosis and clinical management of epilepsy is of utmost importance for the ILAE. To achieve this mission, the Task Force for Epilepsy Education (EpiEd) developed a competency-based curriculum for epileptology, covering the spectrum of skills and knowledge for best medical practice. The curriculum encompasses seven domains, 42 competencies, and 124 learning objectives, divided into three levels: entry (Level 1), proficiency (Level 2), and advanced proficiency (Level 3). A survey of the currently existing ILAE-endorsed teaching activities identified a significant gap in education of basic knowledge of epileptology (Level 1). To bridge this gap, a web-based educational tool is being developed. A virtual campus will be constructed around the curriculum, integrating the various educational activities of the ILAE. This paper describes the development of the curriculum and future tasks necessary to achieve the educational goal of the ILAE.
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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 | 0.023 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".