Bibliographic record
Abstract
In the neonatal period, the majority of seizures are acute reactive events provoked by injury. Some etiologies require immediate diagnosis and treatment. Many of these acute, symptomatic seizures resolve once the underlying etiology is corrected or the acute neurological disruption of the causal event subsides. The electroencephalogram (EEG), amplitude-integrated EEG (aEEG), or quantitative electroencephalography (QEEG) may aid in rapid diagnosis and treatment of clinical and subclinical seizures. The new ILAE classification for neonatal seizures emphasizes the need for EEG for accurate diagnosis. Most EEG patterns in the neonate are non-specific to the etiology of seizures. However, even while non-specific, certain patterns can help direct the diagnostic evaluation. In many cases neuromonitoring may have specific characteristics that are helpful to direct further workup. This chapter discusses neuromonitoring in neonatal seizures due to acute causes, including vascular injury (stroke or hemorrhage), infection, acute metabolic disturbance, brain injury of prematurity, and neonatal abstinence syndrome.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".