© 2010 Canadian Medical Association or its licensors
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is acommon and costly condition worldwide.1,2 A recentglobal population-based study estimated the preva-lence of the disease to be about 10 % among people 40 years of age and older.3 People with known risk factors for COPD, such as increased age and a history of smoking, are likely to have a substanially higher prevalence4–6 and to have progres-sive manifestations of COPD if they continue to smoke.7 They are thus appropriate targets for intervention early in the course of their disease. People with early or undiagnosed COPD are most likely to encounter the health care system in the primary care setting. Consequently, accurate knowledge of the prevalence of COPD in this setting is critical to planning and implementing strategies for the detection and management of the disease. However, valid estimates are lacking of the prevalence of COPD among at-risk individuals in primary care practices. Access by family doctors to spirometric data confirming irre-versible airway obstruction has been shown to influence patient management8 and to enable implementation of a tar-geted self-management plan that may include smoking cessa-tion, pharmacotherapy and increased exercise.9–11 We sought to measure the prevalence of spirometrically confirmed COPD in an at-risk population of adults aged 40 years or more with a smoking history of at least 20 pack-years who visited a primary care practitioner (physician or nurse practitioner) for any reason and to describe their characteris-tics. We also evaluated the accuracy of prior diagnosis or nondiagnosis of COPD and to identify associated clinical characteristics.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.856 | 0.777 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".