DEPLETED URANIUM DUST FROM FIRED MUNITIONS: PHYSICAL, CHEMICAL AND BIOLOGICAL PROPERTIES
Bibliographic record
Abstract
This paper reports physical, chemical and biological analyses of samples of dust resulting from munitions containing depleted uranium (DU) that had been live-fired and had impacted an armored target. Mass spectroscopic analysis indicated that the average atom% of U was 0.198 +/- 0.10, consistent with depleted uranium. Other major elements present were iron, aluminum, and silicon. About 47% of the total mass was particles with diameters <300 microm, of which about 14% was <10 microm. X-ray diffraction analysis indicated that the uranium was present in the sample as uranium oxides-mainly U3O7 (47%), U3O8 (44%) and UO2 (9%). Depleted uranium dust, instilled into the lungs or implanted into the muscle of rats, contained a rapidly soluble uranium component and a more slowly soluble uranium component. The fraction that underwent dissolution in 7 d declined exponentially with increasing initial burden. At the lower lung burdens tested (<15 microg DU dust/lung) about 14% of the uranium appeared in urine within 7 d. At the higher lung burdens tested (~80-200 microg DU dust/lung) about 5% of the DU appeared in urine within 7 d. In both cases about 50% of that total appeared in urine within the first day. DU implanted in muscle similarly showed that about half of the total excreted within 7 d appeared in the first day. At the lower muscle burdens tested (<15 microg DU dust/injection site) about 9% was solubilized within 7 d. At muscle burdens >35 microg DU dust/injection site about 2% appeared in urine within 7 d. Natural uranium (NU) ore dust was instilled into rat lungs for comparison. The fraction dissolving in lung showed a pattern of exponential decline with increasing initial burden similar to DU. However, the decline was less steep, with about 14% appearing in urine for lung burdens up to about 200 microg NU dust/lung and 5% at lung burdens >1,100 microg NU dust/lung. NU also showed both a fast and a more slowly dissolving component. At the higher lung burdens of both DU and NU that showed lowered urine excretion rates, histological evidence of kidney damage was seen. Kidney damage was not seen with the muscle burdens tested. DU dust produced kidney damage at lower lung burdens and lower urine uranium levels than NU dust, suggesting that other toxic metals in DU dust may contribute to the damage.
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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 | 0.000 |
| 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) | 0.000 | 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".