Towards identifying a characteristic neuropsychological profile for fetal alcohol spectrum disorders. 2. Specific caregiver-and teacher-rating.
Bibliographic record
Abstract
OBJECTIVES: This study compares the behavioral profile of children with fetal alcohol spectrum disorder (FASD) who were diagnosed using the Canadian Guidelines with children with prenatal alcohol exposure who did not meet criteria for a FASD diagnosis. METHODS AND PROCEDURES: To accomplish this, we used caregiver and teacher questionnaires evaluating different aspects of behavior. Investigated were 170 children, 109 who received a diagnosis of FASD (Diagnosed Group) and 61 who did not (Non-Diagnosed Group). On the caregiver report, children in the Diagnosed Group had more internalizing and externalizing problems on the CBCL, more executive function difficulties on the BRIEF and more attention problems on the Conner's Rating Scale, compared to the Non-Diagnosed Group. On teacher report, children in the Diagnosed Group had more internalizing and externalizing problems on the TRF and more attention problems on the Conner's Rating Scale, compared to the Non-Diagnosed Group. For both informants, more children in the Diagnosed group had scores in the clinically elevated range. CONCLUSION: Overall, the present results identify key caregiver- and teacher-rated profiles of children with FASD diagnoses. These profiles will aid in better understanding, diagnosing and providing focused treatment approaches for children with FASD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".