An Anomaly in Intercept Time for Short Range Ballistic Re-Entry Vehicles
Bibliographic record
Abstract
This paper documents an anomaly in intercept time of a ballistic re-entry vehicle (RV) by a ballistic interceptor. Intuitively, it is expected that as soon as an incoming RV is detected, the defense will launch an interceptor. However, we show that under some conditions (short range, lofted RV trajectory and an interceptor that is slower than the RV) it is best to delay the launch of the interceptor so that the intercept time is minimal. This is important since by minimizing the intercept time, the interceptor can intercept the RV earlier, further away from the defense location and therefore safer for the defense. In addition, with minimal intercept times, the defense may maximize the number of engagement opportunities. This will allow the defense to improve the probability of raid negation. That is, the probability of neutralizing all incoming RVs is greater with more engagement opportunities. We will show how to minimize the intercept time using analysis in the phase space (velocities of the RV and the interceptor) and validate the results using MANA (Map-Aware Non-uniform Automata).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".