Bibliographic record
Abstract
Nearly a quarter of childhood epilepsy is medically refractory.1 For those children and their families, surgical intervention has the potential to reduce the burden of epilepsy. To address the unique challenges of epilepsy surgery in this population, dedicated multidisciplinary pediatric epilepsy centers have been developed. An expert international consensus panel2 recommended that referral to such centers be considered for all children who are medically refractory or experiencing disabling medication side effects, independent of their cognitive ability or the presence of psychiatric comorbidity. The success of epilepsy surgery depends on several factors, including the underlying etiology and the ability to obtain a complete resection of the epileptogenic zone.3 It has been assumed that technological advances in structural and functional imaging and electroencephalography will result in an improved ability to identify the epileptogenic zone, and thus improved surgical outcomes over time. In this issue of Neurology ®, Hemb et al.4 test this assumption in a comprehensive, retrospective report of surgical outcomes from the well-established UCLA Pediatric Epilepsy Surgery Program from 1986 through 2008. In this follow-up to a prior publication from …
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.007 |
| 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".