Construct and factorial validity of Neurobehavioral Disorder associated with Prenatal Alcohol Exposure (ND-PAE)
Bibliographic record
Abstract
BACKGROUND: ND-PAE, as a condition needing further study, requires validation. Few studies have assessed the validity of ND-PAE with none using a prospective sample. METHODS: Fifty-eight children underwent multidisciplinary FASD assessments and were evaluated for ND-PAE using a prospective, clinical approach. Construct and factorial validity of ND-PAE were assessed, and associations between domains and symptoms described. Post hoc analysis assessed external validity of factors. RESULTS: ND-PAE demonstrated weak construct validity with variable convergence and divergence within and between symptoms. Factor analysis revealed one strong factor consisting of abilities associated with adaptive behavior and general cognitive ability. Relative contribution of symptoms and domains were variable. CONCLUSION: This study provides an evidence-based approach to assessing ND-PAE symptoms and is a starting point to elucidating its neurobehavioral pattern.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".