Introduction to Department of Defense Research on Burn Pits, Biomarkers, and Health Outcomes Related to Deployment in Iraq and Afghanistan
Bibliographic record
Abstract
OBJECTIVE: This paper provides an overview of our study that was designed to assess the health impact of environmental exposures to open pit burning in deployed troops. METHODS: The rationale for the study and the structure of the research plan was laid out. An overview of each article in the supplement was provided. The cohort of deployed Service members was assessed for airborne exposure, relevant biomarkers, and health outcomes following deployment to Balad, Iraq, and/or Bagram, Afghanistan. RESULTS: Polycyclic aromatic hydrocarbon (PAH) exposures were elevated, and serum biomarkers were statistically different postdeployment. Associations were noted between PAHs and dioxins and microRNAs. Some health outcomes were evident in deployers compared with nondeployers. CONCLUSIONS: Future research will examine the associations between demographic variables, smoking status, biomarker levels, and related health outcomes.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".