The 3G Multigenerational Cohort of Nova Scotian women and their mothers and offspring
Bibliographic record
Abstract
BACKGROUND: The negative impact of exposures such as maternal obesity, excessive gestational weight gain, and hypertension in pregnancy on the health of the next generation has been well studied. Evidence from animal studies suggests that the effects of in utero exposures may persist into the second generation, but the epidemiological literature on the influence of pregnancy-related exposures across three generations in humans is sparse. OBJECTIVES: This cohort was established to investigate associations between antenatal and perinatal exposures and health outcomes in women and their offspring. POPULATION: The cohort includes women who were born and subsequently had their own pregnancies in the Canadian province of Nova Scotia from 1980 onward. DESIGN: Intergenerational linkage of data in the Nova Scotia Atlee Perinatal Database was used to establish a population-based dynamic retrospective cohort. METHODS: The cohort has prospectively collected information on sociodemographics, maternal health and health behaviours, pregnancy health and complications, and obstetrical and neonatal outcomes for two generations of women and their offspring. PRELIMINARY RESULTS: As of October 2018, the 3G cohort included 14 978 grandmothers (born 1939-1986), 16 766 mothers or cohort women (born 1981-2003), and 28 638 children (born 1996-2018). The cohort women were generally younger than Nova Scotian women born after 1980, and as a result, characteristics associated with pregnancy at a younger age were more frequently seen in the cohort women; sampling weights will be created to account for this design effect. The cohort will be updated annually to capture future deliveries to women who are already in the cohort and women who become eligible for inclusion when they deliver their first child. CONCLUSIONS: The 3G Multigenerational Cohort is a population-based cohort of women and their mothers and offspring, spanning a time period of 38 years, and provides the opportunity to study inter- and transgenerational associations across the maternal line.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".