Does the Nonverbal Learning Disabilities (NLD) Scale distinguish between subtypes of pervasive developmental disorder
Bibliographic record
Abstract
The NLD Scale, developed by Rourke in 1993, is an instrument designed to assist in the diagnosis of nonverbal learning disabilities (NLD). The purpose of the present investigation, which uses the NLD Scale, was twofold. The first goal was to evaluate the validity and internal consistency of the NLD Scale, which is a relatively new tool. The second goal was to determine if the NLD Scale could distinguish between individuals from 3 different subtypes of pervasive developmental disorder (PDD): (1) high functioning autism (HFA), (2) Asperger syndrome (AS) and (3) pervasive developmental disorder-not otherwise specified (PDD-NOS). This was done in order to investigate recent findings that the NLD neuropsychological profile is characteristic of persons with AS, but not those with HFA. Next, the PDD groups were compared using one-way between groups ANOVAs and Jonckheere's test of trend on each of the following NLD Scale measures: (1) neuropsychological functioning, (2) academic achievement, (3) social-emotional and adaptive functioning, (4) total scores, and (5) individual questions. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 40-03, page: 0791. Adviser: Byron Rourke. Thesis (M.A.)--University of Windsor (Canada), 2001.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".