Bibliographic record
Abstract
Cell-DEVS is an extension to the DEVS formalism that allows the definition of cellular models. CD++ is a modeling and simulation tool that implements Discrete Event Simulation (DEVS) and Cell-DEVS formalisms. The methodology proposed in this paper uses the Cell-DEVS formalism and C++ tool chain [4, 5] to model Uninhabited Aerial Vehicle (UAV) search in a dynamic intelligence environment. Algorithms proposed in previous works [1] were applied to modify the intelligence environment over time. The UAV search pattern was based on this information and the resulting simulation demonstrates emergent UAV search patterns in this intelligence environment. Rule sets model the degradation of this intelligence over time using algorithms proposed in [1], are referred to as a diffusion algorithm; the UAV traversed this map using a hill-climbing algorithm. The resulting UAV search pattern showed preference for the local maximum of target location probability before total maximum to produce an intuitive search pattern. The Cell-DEVS architecture and CD++ tool chain provided a robust development and visualization environment suited to this research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.007 | 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".