Bibliographic record
Abstract
Children and adolescents with epilepsy are known to have high rates of behavior, psychiatric and other co-morbidities. Apart from seizure control, two of the most important factors in determining how well a child progresses toward independence are cognition and behavior. For no other type of epilepsy is it more severe than for children with epileptic encephalopathies. One of the earliest of the age dependent encephalopathies, infantile spasms, has long been associated with a high incidence of mental retardation even in patients who become seizure free by treatment and whose EEG becomes normal. There is emerging evidence that early effective treatment may improve outcome in terms of cognition and behavior. Autism has been reported in cryptogenic cases and an association with temporal lobe tubers in tuberous sclerosis described. In Severe Myoclonic Epilepsy of Infancy, Dravet Syndrome, a variety of psychiatric disorders have been reported including hyperactivity and autistic features. The behavioral problems reported with Lennox-Gastaut Syndrome at disease onset include hyperkinesias, autistic and even psychotic traits. There is often an arrest in development with progressive intellectual impairment. They rapidly develop difficulties with motor speed, apathy, slowness and slow expression. Autistic features, aggression, and hyperkinesis described with Landau-Kleffner Syndrome had often shown dramatic improvement with appropriate treatment. Conclusion: In many children, these co-morbidities are more problematic than the epilepsy itself, and result in poor quality of life for both the child and family. Behavioral and emotional co-morbidities may hinder social integration, which is already problematic in children with epilepsy due to stigma. Difficulties with attention may further limit academic achievement in a population already at risk of developmental delay.
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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 | 0.001 | 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) | 0.006 | 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".