Modified Cooper Harper Scales for Assessing Unmanned Vehicle Displays
Bibliographic record
Abstract
Unmanned vehicle (UV) displays are often the only information link between operators and vehicles, so their design is critical to mission success. However, there is currently no standardized methodology for operators to subjectively assess a display’s support of mission tasks. This paper proposes a subjective UV display evaluation tool: the Modified Cooper-Harper for Unmanned Vehicle Displays (MCH-UVD). The MCH-UVD is adapted from the Cooper-Harper aircraft handling scale by shifting focus to support of operator information processing. An experiment was conducted to evaluate and refine the MCH-UVD, as well as assess the need for mission-specific versus general versions. Participants (86%) thought that MCH-UVD helped them identify display deficiencies, and 32 % said that they could not have identified the deficiencies without the tool. No major additional benefits were observed with mission-specific versions over the general scale.
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How this classification was reachedexpand
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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 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; both teacher heads agree on what is shown here.
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".