Intelligence and Academic Achievement of Adolescents with Craniofacial Microsomia
Bibliographic record
Abstract
BACKGROUND: The authors compared the IQ and academic achievement of adolescents with craniofacial microsomia (cases) and unaffected children (controls). Among cases, the authors analyzed cognitive functioning by facial phenotype. METHODS: The authors administered standardized tests of intelligence, reading, spelling, writing, and mathematics to 142 cases and 316 controls recruited from 26 cities across the United States and Canada. Phenotypic classification was based on integrated data from photographic images, health history, and medical chart reviews. Hearing screens were conducted for all participants. RESULTS: After adjustment for demographics, cases' average scores were lower than those of controls on all measures, but the magnitude of differences was small (standardized effect sizes, -0.01 to -0.3). There was little evidence that hearing status modified case-control group differences (Wald p > 0.05 for all measures). Twenty-five percent of controls and 38 percent of cases were classified as having learning problems (adjusted OR, 1.5; 95 percent CI, 0.9 to 2.4). Comparison of cases with and without learning problems indicated that those with learning problems were more likely to be male, Hispanic, and to come from lower income, bilingual families. Analyses by facial phenotype showed that case-control group differences were largest for cases with both microtia and mandibular hypoplasia (effect sizes, -0.02 to -0.6). CONCLUSIONS: The highest risk of cognitive-academic problems was observed in patients with combined microtia and mandibular hypoplasia. Developmental surveillance of this subgroup is recommended, especially in the context of high socioeconomic risk and bilingual families. Given the early stage of research on craniofacial microsomia and neurodevelopment, replication of these findings is needed. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, II.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".