Simulator Study of Helmet-Mounted Symbology System Concepts in Degraded Visual Environments
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: A sudden loss of external visual cues during critical phases of flight results in spatial disorientation. This is due to undetected horizontal and vertical drift when there is little tolerance for error and correction delay as the helicopter is close to the ground. Three helmet-mounted symbology system concepts were investigated in the simulator as potential solutions for the legacy Griffon helicopters. METHOD: Thirteen Royal Canadian Air Force (RCAF) Griffon pilots were exposed to the Helmet Display Tracking System for Degraded Visual Environments (HDTS), the BrownOut Symbology System (BOSS), and the current RCAF AVS7 symbology system. For each symbology system, the pilot performed a two-stage departure and a single-stage approach. The presentation order of the symbology systems was randomized. Objective performance metrics included aircraft speed, altitude, attitude, and distance from the landing point. Subjective measurements included situation awareness, mental effort, perceived performance, perceptual cue rating, and NASA Task Load Index. Repeated measures analysis of variance and subsequent planned comparison for all the objective and subjective measurements were performed between the AVS7, HDTS, and BOSS. RESULTS: Our results demonstrated that HDTS and BOSS showed general improvement over AVS7 in two-stage departure. However, only HDTS performed significantly better in heading error than AVS7. During the single-stage approach, BOSS performed worse than AVS7 in heading root mean square error, and only HDTS performed significantly better in distance to landing point and approach heading than the others. DISCUSSION: Both the HDTS and BOSS possess their own limitations; however, HDTS is the pilots' preferred flight display.
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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