RESEARCH ARTICLE Open Access Occupational exposure to
Bibliographic record
Abstract
Full list of author information is available at the end of the articleLung cancer continues to be the leading cause of cancer among Canadian men, and in 2012, it was estimated that 13,300 men would be diagnosed with lung cancer and 10,800 would die of it [1]. While cigarette smoking is recognized as the leading cause of lung cancer, many oc-cupational exposures, including asbestos, have also been shown to increase risk. Asbestos is a term used to chrysotile, accounts for 95 % of the asbestos ever used worldwide, and until recently was the only type produced in Canada [2]. All forms of asbestos have long been recognized as human carcinogens by the United States Environmental Protection Agency [3], the International Agency for Research on Cancer [4], and the National Toxicology Program [5]. This conclusion is based largely on unequivocal evidence assembled from epidemiological studies that have found excesses of lung cancer and meso-thelioma in highly exposed textile workers, miners, and cement factory workers [4,6].
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.623 | 0.306 |
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".