Decision-Centred Visualisations for Tactical Decision Support on a Modern Frigate
Bibliographic record
Abstract
Decision support is a focus of attention for the mid-life upgrade of the Combat Control System (CCS) of the Canadian Navy’s HALIFAX Class frigate. We are exploring concepts for developing decision aids to assist the ship’s Command Team with tactical Command and Control. This paper proposes a nonlinear, empirical framework for the investigation. It then gives an overview of work aimed at assessing the feasibility and value for its analysis and design activities of a Cognitive Systems Engineering framework, known as Cognitive Work Analysis (CWA), for modeling intrinsic work demands and determining computer-based support interventions incorporating advanced decision aids to support these demands. It focuses on one aspect of the CWA feasibility study looking at the use of CWA for deriving decision-centred visualisations to enhance operators’ situation awareness and action responses. This leads to preliminary requirements for an interface for the ship’s tactical coordinator that have been captured in a storyboard.
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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 | 0.004 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".