Neuropsychological Assessment for Temporal Lobe Epilepsy Surgery
Bibliographic record
Abstract
Neuropsychological assessment consists of a comprehensive evaluation of cognitive functioning and most often some evaluation of motor skills and sensory status also. Cognitive functions sampled typically include "intelligence" (IQ tests), attention, language skills, visuospatial abilities, "executive skills" and other abilities associated with frontal-lobe function, and learning and memory. Thus, the assessment samples vary widely among a variety of functions, providing a comprehensive picture of an individual's strengths and weaknesses. The resulting pattern points to the probable site of epileptic focus. Neuropsychological findings also serve to predict the risk for postsurgical cognitive decline and, when performance before and after operation is compared, they provide data on the impact of surgery upon cognitive functioning. Comprehensive evaluation of learning and memory is particularly important in this context, because of the frequency of temporal lobe epilepsy and the prominence of memory dysfunction associated with it. In addition, patients slated for elective surgery may also undergo an intracarotid amobarbital procedure (IAP), which is performed to determine the side of cerebral dominance for language and to test the memory capabilities of each hemisphere alone. All of these specialized neuropsychological tools are discussed in this paper.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".