BEHAVIOR OF VARIABLE DENSITY MUNITIONS UNDER DAM BREAK FORCING
Bibliographic record
Abstract
Munitions or Unexploded Ordnance (UXO) are ammunitions belonging to a larger family of explosives from past military activities. Sea disposal of munitions was a common practice from the late 1800s to 1970 when international conventions put an end to the practice. The exact quantity of munitions dumped into the Oceans globally is unknown due to sparse documentation but conservative estimates of known records stand at 1.6 million tons (Wilkinson, 2017). After decades underwater, some munitions have resurfaced in the nearshore, presumably washed onshore or exhumed by high-energy wave action. Extreme events could be major causes of migration and exposure of UXO in the nearshore. The quantification of variable density munitions behavior in the swash zone remains poorly understood. Biofouling, encrustation, and corrosion can alter the density of the underwater munitions, which consequently impacts the behavior of the munitions in the swash zone. Hence, this experimental study aimed to quantify the behavior of variable density munitions in the swash zone under dam-break scenarios. The findings of the study create more insights into the behavior of variable density munitions in the swash zone and can also serve as validation data for probabilistic models on munitions behavior in the swash zone under extreme events.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".