Endemic infectious diseases and biological warfare during the Gulf War: a decade of analysis and final concerns.
Bibliographic record
Abstract
Infectious diseases were one of the first health threats confronted by Coalition troops deployed to the Arabian desert in August 1990. On the basis of experiences in World War II, the major endemic infectious disease risks were thought to be sandfly fever, cutaneous leishmaniasis, diarrheal disease, and malaria. Although there was active surveillance, no case of sandfly fever and few other endemic infectious diseases were identified among over 500,000 U.S., British, and Canadian ground troops. In addition, there was no diagnosis of biological warfare (BW) exposure, and BW agents were not detected in clinical, environmental, or veterinary samples. The most common infectious disease problems were those associated with crowding (acute upper respiratory infections) and reduced levels of sanitation (travelers-type diarrhea). Only one endemic infectious disease has been confirmed as causing chronic health problems: visceral Leishmania tropica infection (viscerotropic leishmaniasis). However, this protozoan infection was diagnosed in only 12 U.S. veterans, and no new cases have been identified during the last 8 years. Infectious diseases were not a serious problem for Gulf War troops because of extensive preventive medicine efforts and favorable weather and geographic factors. Moreover, it is unlikely that an endemic infectious disease or a BW agent could cause chronic health problems and remain undetected over a 10-year period.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".