Abnormal psychomotor development of children. Part II: Electroencephalography
Bibliographic record
Abstract
In paediatric neurology, various pathological conditions, including psychomotor retardation, are assessed in electroencephalography (EEG). This examination is inexpensive, non-invasive and can be repeated multiple times. Moreover, there are no significant contraindications to its performance. The examination consists in registration of brain bioelectrical function with electrodes placed on the surface of the patient’s head in accordance with the international 10–20 system created by Dr Herbert Jasper from the Montreal Neurological Institute. The electrodes are fixed to the patient’s head using conductive gel (applied in order to facilitate the transition of ionic current from the skin surface to the electrode), head band or a special rubber cap which additionally helps with proper location of the electrodes on the patient’s head. In the 10–20 system, even numbers in the electrode markings refer to the right hemisphere, while odd numbers refer to the left hemisphere. The cerebral function recorded during an EEG examination is a result of the motion of electrical loads present in neuronal membranes. The EEG signal recorded during the examination with the use of electrodes is transferred to an electroencephalograph (where it is enhanced) and then, in the digital form, to a computer. Several types of waves are distinguished in EEG: delta, theta, alpha, beta, gamma, mi and lambda. Children are characterised by the variability in the occurrence, range, shape and amplitude of brain waves. EEG involves the use of various activation methods, such as hyperventilation, photic stimulation and sleep deprivation. They are useful in making a proper diagnosis and can be factors that elicit abnormalities that could not be otherwise visualised. Psychomotor retardation is often strictly associated with structural and functional central nervous system abnormalities.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.004 | 0.002 |
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".