Neurocognitive Predictors of Reading Outcomes for Children With Reading Disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study reports on several specific neurocognitive process predictors of reading outcomes for a sample of 278 children with reading disabilities. Three categories of response (i.e., poor, average, and good) were formed via growth curve models of six reading outcomes. Two nested discriminant function analyses were conducted to evaluate the predictive capability of the following models: (a) an intervention and phonological processing model that included intervention group, phonological awareness, and rapid naming and (b) an additive cognitive neuropsychological model that included measures of memory, visual processes, and cognitive or intellectual functioning. Over and above the substantial explanatory power of the base model, the additive model improved classification of poor and good responders. Several of the cognitive and neuropsychological variables predicted degree of reading outcomes, even after controlling for type of intervention, phonological awareness, and rapid naming.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it