Flight-Test of a Tactile Situational Awareness System in a Land-based Deck Landing Task
Bibliographic record
Abstract
The National Research Council of Canada and Defence Research and Development Canada flight-tested the U.S. Naval Aerospace Medical Research Laboratory's Tactile Situational Awareness System (TSAS) in a dynamic task. The TSAS vest uses small pneumatic actuators or ‘tactors’ to transmit information to the pilot. Eleven pilots used the TSAS to cue horizontal axis performance in a land-based deck landing task flown in the NRC Bell 205 helicopter. Pilots tracked a vertically moving target with and without the TSAS in good and degraded visual conditions. The TSAS effectively cued longitudinal fore/aft drifts and reduced RMS error. It had less effect on lateral positioning error, possibly due to the presence of strong visual cues. Pilot situational awareness during degraded visual environment conditions in high sea states was significantly improved by the TSAS, as measured by the China Lake situational awareness rating scale. No change in workload, as measured by Modified Cooper Harper Workload Scale, was attributable to the TSAS use. The improvements in situational awareness and the reduction in longitudinal error suggest that the TSAS would be beneficial for helicopter ship deck landing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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 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".