Evidence of a Healthy Volunteer Effect in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial
Bibliographic record
Abstract
Volunteers for prevention or screening trials are generally healthier and have lower mortality than the general population. The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) is an ongoing, multicenter, randomized trial that randomized 155,000 men and women aged 55-74 years to a screening or control arm between 1993 and 2001. The authors compared demographics, mortality rates, and cancer incidence and survival rates of PLCO subjects during the early phase of the trial with those of the US population. Incidence and mortality from PLCO cancers (prostate, lung, colorectal, and ovarian) were excluded because they are the subject of the ongoing trial. Standardized mortality ratios for all-cause mortality were 46 for men, 38 for women, and 43 overall (100 = standard). Cause-specific standardized mortality ratios were 56 for cancer, 37 for cardiovascular disease, and 34 for both respiratory and digestive diseases. Standardized mortality ratios for all-cause mortality increased with time on study from 31 at year 1 to 48 at year 7. Adjusting the PLCO population to a standardized demographic distribution would increase the standardized mortality ratio only modestly to 54 for women and 55 for men. Standardized incidence ratios for all cancer were 84 in women and 73 in men, with a large range of standardized incidence ratios observed for specific cancers.
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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 | 0.021 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".