69: Bayley-III Outcomes at 18–21 Months Corrected Age for a Canadian Cohort of Infants Born <29 Weeks Gestation
Bibliographic record
Abstract
The Canadian Neonatal Follow-up Network (CNFUN) monitors the outcomes of infants born <29 weeks gestational age (GA) at 26 neonatal follow-up centres across Canada. The use of a standardized assessment tool, the Bayley Scales of Infant and Toddler Development – Third Edition (Bayley-III), at a common age allows for systematic evaluation of cognitive, language and motor development across sites. To describe the cognitive, language and motor development at 18 to 21 months corrected age (CA) for the cohort of CNFUN preterm infants born April 1 2009 to July 1 2011. Trained and qualified Bayley-III testers administered the assessment of cognitive, language and motor abilities to preterm infants at 18 to 21 months CA. Bayley-III composite scores are normally distributed and have a mean of 100, SD 15. Scores <85 are considered below the normal range and are defined here as indicating impairment. Results are presented by gestational age at birth (GA) and by birthweight (BW) category. Of 2528 infants born <29 weeks GA, 2109 (83.4%) were seen in follow-up at 18 to 21 months CA. Cognitive composite scores were obtained for 1958 (92.8%) infants, language composite scores for 1899 (90.0%), and motor composite scores for 1887 (89.5%). The table shows outcomes by GA and by BW category. A high rate of below normal scores was evident for infants born at younger gestational ages and lower birthweights, indicating impairments at 18 to 21 months corrected age, especially with respect to language and motor development. Gestational age specific data on outcomes at 18 to 21 months will be helpful for counseling.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".