The Quebec Newborn Twin Study at 21
Bibliographic record
Abstract
This paper is a revised and updated edition of a previous description of the Quebec Newborn Twin Study (QNTS), an ongoing prospective longitudinal follow-up of a birth cohort of twins born between 1995 and 1998 in the greater Montreal area, Québec, Canada. The goal of QNTS is to document individual differences in the cognitive, behavioral, and social-emotional aspects of developmental health across childhood, their early genetic and environmental determinants, as well as their putative role in later social-emotional adjustment, school, health, and occupational outcomes. A total of 662 families of twins were initially assessed when the twins were aged 6 months. These twins and their family were then followed regularly. QNTS now has 16 waves of data collected or planned, including 5 in preschool. Over the last 24 years, a broad range of physiological, cognitive, behavioral, school, and health phenotypes were documented longitudinally through multi-informant and multimethod measurements. QNTS also entails extended and detailed multilevel assessments of proximal (e.g., parenting behaviors, peer relationships) and distal (e.g., family income) features of the child's environment. QNTS children and a subset of their parents have been genotyped, allowing for the computation of a variety of polygenic scores. This detailed longitudinal information makes QNTS uniquely suited for the study of the role of the early years and gene-environment transactions in development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".