A mirror in the sky: assessment of an augmented reality method for depicting navigational information
Bibliographic record
Abstract
We investigated the efficacy of a novel augmented reality (AR) navigation display called Mirror in the Sky (MitS). AR displays can reduce the distance between virtual imagery content and the user’s view of the environment but may have limited benefit for depicting map-based survey information. MitS presents a simulated mirror in the upper visual field, which reflects the topographic layout of the terrain in front of the user. In our experiment, 28 participants used MitS and a track-up Map in virtual reality to perform a route confirmation task, which required participants to decide whether a route could be successfully navigated. A post-trial threat location recall task examined spatial awareness. On that task, accuracy, duration, and subjective workload measures favoured the Map. However, participants with virtual reality experience made more accurate route confirmation decisions with MitS than the Map. Practitioner summary: We compared an augmented reality display called Mirror in the Sky (MitS) to a conventional electronic map for route confirmation and threat location tasks. Although the electronic map showed advantages over MitS on some measures, users with some VR experience performed route confirmation more accurately with MitS than a map.
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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 | 0.010 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".