3D Cohort Study: The Integrated Research Network in Perinatology of Quebec and Eastern Ontario
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The 3D Cohort Study (Design, Develop, Discover) was established to help bridge knowledge gaps about the links between various adverse exposures during pregnancy with birth outcomes and later health outcomes in children. METHODS: Pregnant women and their partners were recruited during the first trimester from nine sites in Quebec and followed along with their children through to 2 years of age. Questionnaires were administered during pregnancy and post-delivery to collect information on demographics, mental health and life style, medical history, psychosocial measures, diet, infant growth, and neurodevelopment. Information on the delivery and newborn outcomes were abstracted from medical charts. Biological specimens were collected from mothers during each trimester, fathers (once during the pregnancy), and infants (at delivery and 2 years of age) for storage in a biological specimen bank. RESULTS: Of the 9864 women screened, 6348 met the eligibility criteria and 2366 women participated in the study (37% of eligible women). Among women in the 3D cohort, 1721 of their partners (1704 biological fathers) agreed to participate (73%). Two thousand two hundred and nineteen participants had a live singleton birth (94%). Prenatal blood and urine samples as well as vaginal secretions were collected for ≥98% of participants, cord blood for 81% of livebirths, and placental tissue for 89% of livebirths. CONCLUSIONS: The 3D Cohort Study combines a rich bank of multiple biological specimens with extensive clinical, life style, and psychosocial data. This data set is a valuable resource for studying the developmental etiology of birth and early childhood neurodevelopmental outcomes.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it