Characteristics of COPD in never-smokers and ever-smokers in the general population: results from the CanCOLD study
Bibliographic record
Abstract
Background There is limited data on the risk factors and phenotypical characteristics associated with spirometrically confirmed COPD in never-smokers in the general population. Aims To compare the characteristics associated with COPD by gender and by severity of airway obstruction in never-smokers and in ever-smokers. Method We analysed the data from 5176 adults aged 40 years and older who participated in the initial cross-sectional phase of the population-based, prospective, multisite Canadian Cohort of Obstructive Lung Disease study. Never-smokers were defined as those with a lifetime exposure of <1/20 pack year. Logistic regressions were constructed to evaluate associations for ‘mild’ and ‘moderate-severe’ COPD defined by FEV1/FVC <5th centile (lower limits of normal). Analyses were performed using SAS V.9.1 (SAS Institute, Cary, North Carolina, USA). Results The prevalence of COPD (FEV1/FVC Conclusions The study confirmed the substantial burden of COPD among never-smokers, defined the common and gender-specific risk factors for COPD in never-smokers and provided early insight into potential phenotypical differences in COPD between lifelong never-smokers and ever-smokers. Trial registration number NCT00920348 (ClinicalTrials.gov); study ID number: IRO-93326.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".