Bibliographic record
Abstract
PURPOSE: Various EEG patterns emerge in drowsiness. Intermittent bilateral midfrontal slowing (BFS) and hypnogogic frontal predominant sharply contoured waveforms (HFSC), maximal at (Fz, F3-4, and Fp1-2), are often encountered. These do not meet the criteria for epileptiform discharges. The study objective was to determine the clinical significance of BFS and HFSC. METHODS: Clinical information of children with BFS (n = 49) and HFSC (n = 99) was compared with control subjects with generalized spike-wave (GSW) discharges (n = 102) and normal EEGs (n = 100). RESULTS: HFSC was present in younger children (mean age was 3.5 ± 3.6 years), whereas BFS was present in older children (mean 12.9 ± 4.8 years). Seizures occurred in the normal EEG, BFS, HFSC, and GSW groups, respectively, as follows: 22 (22%), 15 (31%), 42 (43%), and 100 (98%) patients, whereas epilepsy occurred in 17 (17%), 10 (20%), 35 (35%), and 95 (93%) patients. The GSW group had more seizures and epilepsy than the other groups (P < 0.001), but the HFSC group also had more seizures (P < 0.001) and epilepsy (P < 0.003) than the normal EEG group. Seizures and neurodevelopmental and psychiatric comorbidities were similar between the BFS and normal EEG groups. Notably, the HFSC group had more developmental delay than the normal EEG group [33 (33%) versus 18 (18%), P < 0.009] but were similar to the GSW group 22 (22%). CONCLUSIONS: Bilateral midfrontal slowing and HFSC have had unclear significance. Our results suggest that HFSC may be a marker of increased risk of seizure, epilepsy, and developmental delay as compared to children with normal EEGs and has similar risk of developmental delay to those with GSW.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".