Prototype Unmanned System Training Simulator
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a prototype training simulator design developed in response to the expanding student population for unmanned system operators. The projected operators for unmanned systems are now being expanded beyond the traditional focus-group of pilot and pilot trainees. The broadening of the field from which unmanned system operators previously had been selected, and the increased mission support role of operators, also broadens the ground training requirements in order to achieve certification. The backbone of the simulator for this training system is a scalable architecture concept that is softwareintensive with loosely coupled training system elements. This common backbone for scalable application also results in common logistic support, meaning lower life cycle cost. The prototype training device design takes advantage of commercially off-the-shelf (COTS) hardware and software products already proven in fielded platforms. The training system design that responds to these requirements incorporates principles from device-based aircrew training as well as high engagement strategies from simulation and gaming. This design not only enhances unmanned system operator training, but also makes significant advancement of role player in-the-loop mission training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 it