Trends, perinatal characteristics, and medical conditions in pervasive developmental disorders
Bibliographic record
Abstract
Our aim was to study trends in the prevalence of pervasive developmental disorders (PDD) and to quantify their association with morphogenetic anomalies and with perinatal characteristics such as gestational age, birthweight, and hospitalization in a neonatal care unit. Data from a French morbidity register of childhood disabilities with the use of consistent definitions over time within the same geographical area were analyzed. The data of a total of 454 children (312 males, 142 females) with PDD, born between 1980 and 1993 and residing in Isère county, were recorded at the age of 7 years. The overall prevalence of PDD was 22.2 out of every 10000. There was a significant increase, from 14.7 to 30.8 out of every 10 000, during the period of study. Among these children with PDD, morphogenetic anomalies were observed in 12.1% (95% confidence interval [CI] 9.3-15.5), and the hospitalization rate during the neonatal period was 22% (95% CI 17.0-27.5), which is significantly higher than the observed rates in the general population. The increase in the prevalence of PDD, the association with perinatal risk factors, and the high rate of neonatal hospitalization require further studies to investigate the reasons for and mechanisms of these developmental disorders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".