Subhairline EEG in neurocritical care: use and limitations through illustrative cases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Subhairline electroencephalography (EEG) is a limited-montage EEG with applications in epilepsy and neurocritical care. It has potential advantages in resource-limited settings and may help in the early diagnosis and management of seizures and status epilepticus while providing real-time electrophysiological monitoring. It has several important technical limitations such as reduced spatial coverage, low sampling rate, inadequate bit depth and review software with limited features. Clinicians must carefully consider these limitations for proper interpretation and so avoid diagnoses based on false positives or false negatives. We present six cases using subhairline EEG and their corresponding 10-20 EEG recordings to help in pattern recognition and to highlight the usefulness and limitations of this technique.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it