NL research program on protection of field structures against the effects of enhanced blast weapons
Bibliographic record
Abstract
It is acknowledged that blast weapon technology is proliferating and that troops during missions out-of-area are vulnerable for resulting enhanced blast and thermal effects. Therefore, the Netherlands Ministry of Defence has tasked TNO Defence, Security and Safety to define and conduct a four year research program on protection of field structures against the effects of enhanced blast weapons (EBW). This NL research program is strongly related to the four year Canadian Technology Demonstration Program on “Force protection against enhanced blast” [1]. Based on Implementing Arrangement number 22 to the MoU between Canada and The Netherlands [2]. DRDC Suffield and TNO Defence, Security and Safety are sharing and exchanging theoretical and experimental data to develop models to assess structure vulnerability and to define structure countermeasures. This paper describes the NL research program goals, -approach and -deliverables including some preliminary results. A more detailed overview of the results so far is given in the companion paper presented by Rhijnsburger [3].
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.009 |
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".