Classification of the epilepsies: New concepts for discussion and debate—Special report of the ILAE Classification Task Force of the Commission for Classification and Terminology
Bibliographic record
Abstract
The ILAE Task Force on Classification presents a road map for the development of an updated, relevant classification of the epilepsies. Our objective is to explain the process to date and the plan moving forward as well as to invite further discussion about the newly proposed terms and concepts. Here, we present our response to feedback about the 2010 Organization of the Epilepsies and clarify the reintroduction of the word "classification" to map out a framework for epilepsy diagnosis. We introduce some new concepts and suggest four diagnostic levels: seizure type, epilepsy category, epilepsy syndrome, and epilepsy with (specific) etiology to denote specific levels of diagnosis. We expand the etiological categories to six, focusing on those with treatment implications. Finally, we discuss the changes in terminology originally suggested and modifications in response to comments from the epilepsy community. We welcome feedback and discussion from the global epilepsy community, particularly for the new suggested terms, so that we can cement a classification that both reflects current thinking and scientific understanding and provides a dynamic, evolving framework.
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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 | 0.140 | 0.211 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.019 | 0.044 |
| Open science | 0.011 | 0.013 |
| Research integrity | 0.016 | 0.048 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".