Occupational and environmental risk factors of adult primary brain cancers: a systematic review.
Bibliographic record
Abstract
The incidence of brain neoplasm has been progressively increasing in recent years in the industrialized countries. One of the reasons for this increased incidence could be better access to health care and improved diagnosis in the industrialized countries. It also appears that Caucasians have a higher incidence than blacks or Hispanics or Asians. A number of risk factors have been identified and described including the genetic, ethnic and age-based factors. Certain occupational and environmental factors are also believed to influence the risk of primary adult brain tumors. Potential occupational and environmental factors include exposure to diagnostic and therapeutic radiations, electromagnetic radiation from cellular phones and other wireless devices, infectious agents, air pollution and residence near landfills and high-voltage power lines and jobs as firefighters, farmers, physician, chemists and jobs in industries such as petrochemical, power generation, synthetic rubber manufacturing, agricultural chemicals manufacturing. The purpose of this systematic review is to examine occupational and environmental risk factors of brain neoplasm. A range of occupational and environmental exposures are evaluated for significance of their relationship with adult primary brain tumors. On the basis of this review we suggest a concurrent evaluation of multiple risk factors both within and beyond occupational and environmental domains. The concurrent approach needs to consider better exposure assessment techniques, lifetime occupational exposures, genotypic and phenotypic characteristics and lifestyle and dietary habits. This approach needs to be interdisciplinary with contributions from neurologists, oncologists, epidemiologists and molecular biologists. Conclusive evidence that has eluded multitude of studies with single focus and single exposure needs to multifaceted and multidisciplinary.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".