Bibliographic record
Abstract
In both littoral environments and the open ocean, assessing the risk of bullet ricochet from the water surface is important as friendly assets and possibly civilian infrastructure may be in close proximity to operations. Bullet ricochet from water is usually examined in a laboratory environment where bullets are fired at a level water surface. While this set-up is appropriate for replicating ricochet from ponds, puddles, or small water containers, it is less applicable to ricochet from large bodies of water that support a rich surface wave field. Here, a method is proposed to extend results of flat-water experiments to consider bullet ricochet from a wavy surface. It is shown that the critical angle above which ricochet does not occur and the likelihood of stable or tumbling ricochets depend on whether waves are present and in what direction those waves are traveling relative to the path of the incoming bullet. Modeling suggests that the risk of ricochet is reduced when wave crests are perpendicular to the direction of fire but waves also increase the variability of ricochet characteristics. It is therefore suggested that, when possible, wave effects be considered when assessing the risk of bullet ricochet from water.
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".