44(5):520-532,2003 EDITORIAL Undiagnosed Illnesses and Radioactive Warfare
Bibliographic record
Abstract
The internal contaminationwith depleted uranium (DU) isotopeswas detected in British, Canadian, andUnited States GulfWar veterans as late as nine years after inhalational exposure to radioactive dust in the PersianGulfWar I.DU iso-topes were also identified in a Canadian veteran’s autopsy samples of lung, liver, kidney, and bone. In soil samples from Kosovo, hundreds of particles, mostly less than 5 m in size, were found in milligram quantities. Gulf War I in 1991 resulted in 350 metric tons of DU deposited in the environment and 3-6 million grams of DU aerosol released into the atmosphere. Its legacy, Gulf War disease, is a complex, progressive, incapacitating multiorgan system disor-der. The symptoms include incapacitating fatigue,musculoskeletel and joint pains, headaches, neuropsychiatric disor-ders, affect changes, confusion, visual problems, changes of gait, loss of memory, lymphadenopathies, respiratory im-pairment, impotence, and urinary tractmorphological and functional alterations. Current understanding of its etiology seems far from being adequate. After the AfghanistanOperation Anaconda (2002), our team studied the population of Jalalabad, SpinGar, ToraBora, andKabul areas, and identified civilianswith the symptoms similar to thoseofGulfWar syndrome. Twenty-four-hour urine samples from 8 symptomatic subjects were collected by the following criteria: 1) the onset of symptoms relative to the bombing raids; 2) physical presence in the area of the bombing; and 3) clinical manifestations. Control subjects were selected among the sympotom-free residents in non-targeted areas. All samples were analyzed for the concentration and ratio of four uranium isotopes, 234U, 235U, 236U and 238U, by using a
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.023 | 0.017 |
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".