Interrelations between maternal smoking during pregnancy, birth weight and sociodemographic factors in the prediction of early cognitive abilities
Bibliographic record
Abstract
Maternal prenatal smoking, birth weight and sociodemographic factors were investigated in relation to cognitive abilities of 1544 children (aged 3.5 years) participating in the Québec Longitudinal Study of Children's Development. The Peabody Picture Vocabulary Test (PPVT) was used to assess verbal ability, the Wechsler Preschool and Primary Scale of Intelligence-Revised (WPPSI-R) block design test to assess visuospatial ability, and the Visually Cued Recall (VCR) task to assess short-term memory. Prenatal smoking was related to performance on the WPPSI-R, the PPVT, and the VCR, although it did not independently predict any cognitive ability after maternal education was taken into account. Birth weight was a more robust predictor of all outcome measures and independently predicted VCR-performance. Birth weight interacted significantly with family income and maternal education in predicting visuospatial ability, indicating a greater influence of birth weight under relatively poor socio-economic conditions. Parenting and family functioning mediated associations between maternal education/family income and cognitive task performance under different birth weight conditions, although there were indications for stronger effects under relatively low birth weight. We conclude that investigations of moderating and mediating effects can provide insights into which children are most at risk of cognitive impairment and might benefit most from interventions.
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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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".