Training effectiveness and validation of a VR HMD-based simulator for air force pilots
Bibliographic record
Abstract
Virtual reality (VR) head-mounted display (HMD) was examined for Air Force training modernisation. In Experiment 1 (E1), Novice pilots performed the Overhead break (OHB) manoeuvre and flight proficiency scores were measured and compared to Expert pilots OHB performance in a VR HMD-based simulator. Cybersickness was also measured. Experts performed significantly better on the OHB manoeuvre than Novices. Both groups improved significantly over the course of the experiment and cybersickness was negligible. E1 indicated that the VR HMD flight trainer can be valid, effective and safe for training the OHB maneuvre. Experiment 2 (E2) compared an established Flight Training Device (FTD; not the VR simulator) and Live Flight OHB scores for Novice pilots from E1 to Novices not in E1. There was no difference in FTD and Live Flight scores between both groups. E2 revealed that completion of E1 was insufficient to translate to superior performance in FTD and Live Flight.
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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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".