Bibliographic record
Abstract
Reflecting the increasing rate of tobacco use in women after World War II, the age-adjusted rate of lung cancer incidence in women has climbed from less than 20 per 100,000 in 1973 to approximately 40 per 100,000 by 1999 [101]. Currently, approximately 20% of women in the USA smoke, with little evidence that the frequency will decline due to antismoking campaigns [1]. The smoking prevalence is highest in younger women, especially those from economically and educationally deprived backgrounds. Although the rate of lung cancer deaths in men has started to decline, it only appears to have slowed its rate of increase in women, who now account for more than 40% of lung cancer deaths [2]. In the USA, lung cancer-related deaths in women now exceed those from breast or colon cancer combined [3]. Women may be more susceptible to the carcinogenic effects of tobacco smoke than men. This has been demonstrated epidemiologically, as well as in laboratory and clinical studies. In a study in 800 Canadian women, the association of smoking and nonsmall-cell lung cancer (NSCLC) was significantly stronger for females than for males [4]. In subjects with a history of 40 packyears, compared with lifelong nonsmoking, the odds ratio for women to develop lung cancer was 27.9 (95% confidence interval [CI]: 14.9–52.0) and for men was 9.60 (95% CI: 5.64–16.3). Higher odds ratios for females were also seen within each of the major histological groupings. Thus, the elevated risk of lung cancer currently observed in other studies for female ever-smokers compared with male ever-smokers may be due to higher susceptibility among females. A case–control study of 4000 patients and control subjects was conducted in the USA [5]. The
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".