Invitation to participate in a prospective case–control study of sudden unexpected death in epilepsy
Bibliographic record
Abstract
Invitation to participate in a prospective Case-control study of SUDEPThe EpiNet study group is undertaking a Case-control study of SUDEP and is inviting physicians looking after people with epilepsy to participate.The study is being performed prospectively.We hope to identify 200 cases of SUDEP.Since SUDEP is not very common, we will need to get multiple centres involved.Relatives of cases will be interviewed, and medical records reviewed to learn as much as possible about the circumstances of death, the individual's epilepsy, its treatment, and lifestyle issues.For each case we will also identify 3 age and sex-matched controls from the same centre, who will also be interviewed.Finally, we will interview one proxy control, who will be a relative of one of the control subjects with epilepsy.SUDEP cases are going to be collected prospectively.At the outset, each centre will need to identify a cohort from which cases and controls will be identified.The nature of the cohort may vary from centre to centre, but it needs to be defined at the outset, and cases and controls must come from this cohort.New people with epilepsy can join the cohort during the course of the study, and only people who are alive at the time the study starts can be included.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.021 |
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".