Bibliographic record
Abstract
A key component in any soft-kill response to an incoming guided missile is the flare /chaff decoy used to distract or seduce the seeker homing system away from the naval platform. This paper describes a new 3D flare particle model in the naval threat countermeasure simulator (NTCS) of the NATO-standard ship signature model (ShipIR), which provides independent control over the size and radial distribution of its signature. The 3D particles of each flare sub-munition are modelled stochastically and rendered using OpenGL z-buffering, 2D projection, and alpha-blending to produce a unique and time varying signature. A sensitivity analysis on each input parameter provides the data and methods needed to synthesize a model from an IR measurement of a decoy. The new model also eliminated artifacts and deficiencies in our previous model which prevented reliable tracks from the adaptive track gate algorithm already presented by Ramaswamy and Vaitekunas (2015). A sequence of scenarios are used to test and demonstrate the new flare model during a missile engagement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".