Laser Interstitial Thermal Therapy (LITT) for Insular Epilepsy
Bibliographic record
Abstract
Compared to surgery, LITT provides minimal disruption of the brain matter, less post-operative pain and shorter length of stay. LITT has enabled a more minimalist approach to deep-seated targets such as the insula. Increasing utilization of stereoelectroencephalography has allowed for better identification of seizure onset involving the insular cortex and subsequent ablation, including many patients with prior surgeries involving the frontal, parietal, and temporal lobes. The insula serves as an ideal target for LITT, given the deep location and surrounding anatomic structures. There are limited studies on the efficacy of LITT in adults with lesional or non-lesional insular epilepsy. Retrospective LITT studies as well as comparisons with open surgical resection in the pediatric population have, however, shown good comparative efficacy while also demonstrating minimal, often transient, post-operative complications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".