Bibliographic record
Abstract
Several recent articles re-emphasize the value of clinical electrophysiology: in localizing epileptogenesis, predicting effectiveness of epilepsy surgery, and disclosing a mechanism of benign Rolandic epilepsy of childhood.A review of the role of EEG in the diagnosis of epilepsy indicated that epileptiform activity will appear in 50% of initial awake recordings of adults with epilepsy and in 85% of subjects undergoing two recordings. This contrasts with the appearance of spikes in only 4 of 1000 normal persons. Several studies focused on the value of electroencephalography in extratemporal epilepsy: 62% of patients with neocortical epilepsy had at least one localizing ictal EEG; occipital and temporal neocortical seizures were localized in a greater proportion than frontal or parietal attacks. Interictal spikes, if unifocal, always arose from the epileptogenic region in a study of their seizure localizing value. Such congruence augured for better seizure control by focal resection in two studies reviewed herein. Studies indicating the value of interictal temporal lobe spikes and scalp-recorded seizures in lateralising a temporal seizure focus are reviewed. One study found EEG to be slightly more reliable for lateralization of temporal epileptogenesis than MRI. In patients with benign Rolandic seizures, enhanced motor evoked potentials (MEPs) were obtained from transcranial magnetic stimulation when this was applied 50-80 msec after electrical stimulation of the thumb whereas this interval inhibited the MEP in normal subjects. This suggests that afferent cutaneous input abnormally and synchronously activates a large population of sensory neurons; such activation is subsequently transmitted to the motor cortex to produce the focal spikes in this condition.Finally, advances in non-invasive technology have redefined and limited the need for invasive monitoring in children with intractable seizure disorders.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.035 | 0.028 |
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".