Bibliographic record
Abstract
Summary Criticized by many as the new “weapon of mass destruction,” lauded by some as the “weapon of choice in combat,” the use of depleted uranium ammunition in warfare raises many legal questions. Designed as a point weapon to penetrate armoured targets, scientific studies prove that depleted uranium has both chemically and radioactively toxic characteristics. Clearly, every weapon of war will have some affect on human health and the environment, but the laws of armed conflict have evolved to place limits on the level of harm viewed as permissible and legal. Does this “weapon of choice,” therefore, breach the international laws of armed conflict? Although the subject of media frenzy in the immediate aftermath of the 1999 Kosovo conflict, the use of depleted uranium ammunition in Iraq 2003 raised little media attention. How could the use of such a controversial weapon in 1991 go largely unnoticed just four years later? Does this lack of global condemnation necessarily lead to the conclusion that the “dictates of the public conscience” have evolved in regard to the use of this previously controversial weapon of war? This article seeks to analyze the legality of the use of depleted uranium ammunition — the main question being whether the existing laws of armed conflict are already sufficient to address any human and environmental concerns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".