[Neuropsychological characteristics of selective attention in children with nonverbal learning disabilities].
Bibliographic record
Abstract
OBJECTIVE: To investigate the neuropsychological characteristics of selective attention such as attention control, working memory and attention persistence of frontal lobe in children with nonverbal learning disabilities (NLD). METHODS: With Auditory Detection Test (ADT), Wisconsin Card Sorting Test (WCST) and C-WISC, 14 children with NLD and 23 controls were tested and the results of sub-tests of C-WISC were analyzed with factor analysis. ADT was mainly applied to test the ability of auditory discernment and the function of dominance lateralization in the cerebra; WCST was employed to test the function of working memory which was based on the frontal lobe, and, C-WISC, to test the intelligent structure and characteristics. RESULTS: Compared with control group, the correct response rate of ADT in NLD group was much lower (P < 0.01), and the number of incorrect response was much larger (P < 0.01). Children with NLD had deficits of auditory selective attention. Moreover, the number of categories achieved (CA) and perseverative error (PE) of WCST were much lower (P < 0.05), which indicated that children with NLD had the disorders of selective attention and performance function. Factor analysis showed that perceptual organization (PO) related to visual space and freedom from distractibility (FD) related to attention persistence in NLD group were obviously lower than those in control group (P < 0.01, P < 0.05). These findings further supported the above-mentioned results. CONCLUSIONS: Children with NLD had attention control disorder and working memory disorder mainly in frontal lobe; we suppose that the disorder in right frontal lobe was distinctive.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".