An improved estimate of the quantitative relationship between polycyclic hydrocarbons and lung cancer
Bibliographic record
Abstract
In this issue of the journal, Armstrong and Gibbs ( see page 740 ) report the updated results from a mortality study of a large cohort of Quebec aluminium smelter workers.1 2 The focus of their analysis is the quantitative relationship between exposure to polycyclic aromatic hydrocarbons (PAHs) and mortality from lung cancer. Ten more years of follow-up were added along with new cohorts from additional smaller plants for comparison with previously published data3; the study is now the largest ever conducted in aluminium smelting, with 16 431 individuals followed since as far back as 1950 and 677 observed lung cancer deaths.4 More importantly, individual job histories and smoking habits have been recovered, and historical measurements of exposure to benzo[a]pyrene (BaP) and benzene-soluble matter (BSM) could be used to develop a job-exposure matrix (JEM). By applying the JEM, cumulative exposures to BaP and BSM were calculated at the individual level.5 Thus, both statistical power and high quality exposure data were obtained by Armstrong and Gibbs. A new estimate of the slope (and …
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".