Bibliographic record
Abstract
Intractable seizures can have a devastating effect on the development of a child. In children with intractable epilepsy that is refractory to medication, surgical treatment may be needed. Magnetic resonance imaging is an essential neuroimaging tool to assist in the identification of an epileptogenic substrate. The interpretation of MR images should be done in the context of clinical knowledge of the seizure symptomatology and electroencephalographic findings. Quantitative processing of structural MR data and advanced MR imaging such as diffusion tensor imaging and MR spectroscopy have the potential to identify subtle lesions that may otherwise have been missed. In addition to lesion localization, identification of eloquent cortex and white matter tracts are also an essential component of epilepsy surgery workup. Functional MR imaging maps the sensorimotor cortex and also lateralizes language. Diffusion tensor imaging tractography can be used to map the corticospinal tracts and the optic radiations. In addition to MR imaging, magnetoencephalography and nuclear medicine studies such as PET and SPECT scanning may be used to lateralize seizure focus when clinical, electrophysiological, and structural MR imaging findings are discordant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".