Bibliographic record
Abstract
Evidence from a recent randomized controlled trial of surgical versus medical therapy of temporal lobe epilepsy proves that antero-mesial resection is safe and more effective than medical therapy. The number of patients needed to treat for one patient to become free of disabling seizures is two, which is superior to most interventions in neurology. A meta-analysis of non-randomized trials gives almost identical results; about two-thirds of patients become seizure-free, compared with only 8% with medical therapy. The results are remarkably similar among studies from different parts of the world. Quality of life improves early after epilepsy surgery, the improvements are both statistically and clinically significant, and they are sustained. Surgical morbidity with clinically important permanent sequelae is 2%. Epilepsy surgery remains underutilized in developed countries and it does not exist in all but a few developing countries. Current randomized trials are underway to explore the effect of early surgery versus optimum medical therapy on the prevention of disability in patients with mesial temporal lobe epilepsy, and to examine the effectiveness of novel interventions, such as minimally invasive surgery and brain stimulation.
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.
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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".