Lead exposure and motor functioning in 4½ -year-old children: The Yugoslavia Prospective Study
Bibliographic record
Abstract
OBJECTIVE: To investigate associations between lead exposure and early motor development. STUDY DESIGN: We conducted standardized assessments of motor function (Bruininks-Oseretsky Test of Motor Proficiency and Beery Developmental Test of Visual-Motor Integration) at age 54 months in 283 children whose mothers were recruited in pregnancy from a smelter town and a non-lead-exposed town in Yugoslavia and who have been monitored twice yearly since birth. Blood lead concentration (BPb) was summarized in a measure reflecting the average of the child's semiannual serial log BPbs through 54 months. RESULTS: Multiple regression showed that taken together, anthropometric measures (birth weight, body mass index) and markers of a stimulating and organized home life (HOME scale, parental education and intelligence, availability of siblings) explained a significant 10% to 18% of the variance in motor functioning. Beyond these contributions, BPb was significantly associated with poorer fine motor and visual motor function but was unrelated to gross motor coordination. CONCLUSIONS: Modest associations between early lead exposure and fine motor and visual motor functioning appear even after statistical adjustment is done for other contributors to motor development. Associations with BPb are specific to these areas of motor skill; gross motor development was unaffected.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".