Prenatal and early-life predictors of atopy and allergic disease in Canadian children: results of the Family Atherosclerosis Monitoring In earLY life (FAMILY) Study
Bibliographic record
Abstract
Prenatal and early-life environmental exposures play a key role in the development of atopy and allergic disease. The Family Atherosclerosis Monitoring In earLY life Study is a general, population-based Canadian birth cohort that prospectively evaluated prenatal and early-life traits and their association with atopy and/or allergic disease. The study population included 901 babies, 857 mothers and 530 fathers. Prenatal and postnatal risk factors were evaluated through questionnaires collected during the antenatal period and at 1 year. The end points of atopy and allergic diseases in infants were evaluated through questionnaires and skin prick testing. Key outcomes included atopy (24.5%), food allergy (17.5%), cow's milk allergy (4.8%), wheezing (18.6%) and eczema (16%). The association between infant antibiotic exposure [odds ratio (OR): 2.04, 95% confidence interval (CI): 1.45-2.88] and increased atopy was noted in the multivariate analysis, whereas prenatal maternal exposure to dogs (OR: 0.60, 95% CI: 0.42-0.84) and acetaminophen (OR: 0.68, 95% CI: 0.51-0.92) was associated with decreased atopy. This population-based birth cohort in Canada demonstrated high rates of atopy, food allergy, wheezing and eczema. Several previously reported and some novel prenatal and postnatal exposures were associated with atopy and allergic diseases at 1 year of age.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".