Longitudinal follow-up of the asthma status in a French–Canadian cohort
Bibliographic record
Abstract
Abstract Asthma affects 340 million people worldwide and varies in time. Twenty years ago, in Canada, the Saguenay–Lac-Saint-Jean asthma family cohort was created to study the genetic and environmental components of asthma. This study is a follow-up of 125 participants of this cohort to explore the appearance, persistence, and progression of asthma over 10–20 years. Participants answered a clinical standardized questionnaire. Lung function was assessed (forced expiratory volume in 1 s, forced vital capacity, bronchial reversibility, and methacholine bronchoprovocation), skin allergy testing was performed, blood samples were obtained (immunoglobulin E, white blood cell counts) and phenotypes were compared between recruitment and follow-up. From the participants without asthma at recruitment, 12% developed a phenotype of adult-onset asthma with the presence of risk factors, such as atopy, high body mass index, and exposure to smoking. A decrease of PC20 values in this group was observed and a decrease in the FEV1/FVC ratio in all groups. Also, 7% of individuals with asthma at recruitment developed chronic obstructive pulmonary disease, presenting risk factors at recruitment, such as moderate-to-severe bronchial hyperresponsiveness, exposure to smoking, and asthma. This study allowed a better interpretation of the evolution of asthma. Fine phenotypic characterization is the first step for meaningful genetic and epigenetic studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".