Smoking-related idiopathic interstitial pneumonia
Bibliographic record
Abstract
Cigarette smoking is a key factor in the development of numerous pulmonary diseases. An international group of clinicians, radiologists and pathologists evaluated patients with previously identified idiopathic interstitial pneumonia (IIP) to determine unique features of cigarette smoking. Phase 1 (derivation group) identified smoking-related features in patients with a history of smoking (n=41). Phase 2 (validation group) determined if these features correctly predicted the smoking status of IIP patients (n=100) to participants blinded to smoking history. Finally, the investigators sought to determine if a new smoking-related interstitial lung disease phenotype could be defined. Phase 1 suggested that preserved forced vital capacity with disproportionately reduced diffusing capacity of the lung for carbon monoxide, and various radiographic and histopathological findings were smoking-related features. In phase 2, the kappa coefficient among clinicians was 0.16 (95% CI 0.11-0.21), among the pathologists 0.36 (95% CI 0.32-0.40) and among the radiologists 0.43 (95% CI 0.35-0.52) for smoking-related features. Eight of the 100 cases were felt to represent a potential smoking-related interstitial lung disease. Smoking-related features of interstitial lung disease were identified in a minority of smokers and were not specific for smoking. This study is limited by its retrospective design, the potential for recall bias in smoking history and lack of information on second-hand smoke exposure. Further research is needed to understand the relationship between smoking and interstitial lung disease.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".