Malignant Tumors of the Female Reproductive System
Bibliographic record
Abstract
This review summarizes the epidemiology of cancer of the female reproductive system and associated lifestyle factors. It also assesses the available evidence for occupational factors associated with these cancers. Cervical, endometrial, and ovarian cancers are relatively common, and cause significant cancer morbidity and mortality worldwide, whereas vulvar, vaginal, fallopian tube cancers, and choriocarcinomas are very rare. As several lifestyle factors are known to play a major role in the etiology of these cancers, very few published studies have investigated possible relationships with occupational factors. Some occupational exposures have been associated with increased risks of these cancers, but apart from the available evidence on the relationships between asbestos fibers and ovarian cancer, and tetrachloroethylene and cervical cancer, the data is rather scarce. Given the multifactorial nature of cancers of the female reproductive system, it is of the utmost importance to conduct occupational studies that will gather detailed data on potential individual confounding factors, in particular reproductive history and other factors that influence the body's hormonal environment, together with information on socio-economic status and lifestyle factors, including physical activity from multiple sources. Studies on the mechanisms of carcinogenesis in the female reproductive organs are also needed in order to elucidate the possible role of chemical exposures in the development of these 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 | 0.001 |
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".