A Communications-based Mission Planning Tool Concept for Low-cost Tactical UXV Operations
Bibliographic record
Abstract
Abstract : New concepts for communications-based tactical decision aids, which can be used for low-costtactical UXV operations, are investigated to provide input for future mission planning tools thatcould be developed for the Royal Canadian Navy. The proposed tactical decision aids provideinformation on where and when communications between a UXV and its base station will beeffective and not effective as a function of the current and future environmental conditions. Therequired signal propagation calculations use data from an Environment Canada numericalweather prediction model and a terrain elevation database. A description is provided of theapproach used to calculate the base quantities (signal-to-noise ratio, , bit error rate) thatare required to form the tactical decisions aids. Example tactical decision aids are calculated fora specific case to demonstrate how this information could be used for planning UXV routes. Theexample case clearly shows regions where communications are effective and not effectivewithin a realistic environment. Experimental trials are required to test the hypothesis that theproposed method is capable of accurately now-casting and forecasting the times and places forwhich a UXV will have effective communication with its base station.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.010 | 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".