Developing User Models for Military Command and Control
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
The Artificial Intelligence Research Group at the Royal Military College of Canada is a key contributor in the development of future command and control systems for the Canadian military. The assumption of user characteristics that influence plan recognition, such as knowledge, beliefs, and preferences is a key focus of our research group. We are developing a user modelling system that will incorporate plan recognition to provide an effective and efficient tool for a commander to plan military operations. 1 Introduction The Royal Military College of Canada conducts research into the use of artificial intelligence techniques for command and control systems. This research is conducted in cooperation with the two Canadian Defence Research Establishments in Valcartier, Quebec and Suffield, Alberta. When the group was first established, research focused on the multibillion dollar Tactical Command, Control, and Communications System. At that time, solutions were sought for a range of probl...
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it