A novel study design to investigate the early‐life origins of asthma in children (SAGE study)
Bibliographic record
Abstract
This is a description of the Study of Asthma, Genes and the Environment (SAGE), a novel birth cohort created from provincial healthcare administrative records. It is a general population-based cohort, composed of children at high and low risk for asthma, living in urban and rural environments in Manitoba, Canada. The SAGE study captures the complete longitudinal healthcare records of children born in 1995 and contains detailed information on early-life exposures, such as antibiotic utilization and immunization, in relationship to the development of asthma. Nested within the birth cohort is a case-control study, which was created to collect information on home environmental exposures from detailed surveys and home dust sampling, to confirm asthma status in children and use this data to validate healthcare database measures of asthma, to determine differences in immune system responsiveness to innate and adaptive immune stimuli in asthma, to genotype children for genes likely associated with the development of asthma and to study the epigenetic regulation of pre-established protective vs allergic immune responses. The SAGE study is a multidisciplinary collaboration of researchers from pediatric allergy, population health, immunology, and genetic and environmental epidemiology. As such, it serves as a fertile, interdisciplinary training ground for graduate students, and postdoctoral and clinician fellows.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".