A Mirror-in-the-Sky Navigation Aid: Summary of Qualitative Feedback from Soldier and Civilian Users
Bibliographic record
Abstract
We tested the efficacy of a novel augmented reality navigation aid, called SkyMap, which presents survey navigation information in the sky, above the user. Soldier and civilian users completed a route following task using Mirror-in-the-Sky (a virtual reality prototype of the SkyMap concept), a north-up map, and a track-up map. In this paper, we analyzed and presented a summary of qualitative user feedback and compare feedback from soldier and civilian users. Specifically we used affinity diagrams to categorize verbal qualitative feedback, which led us to identify six themes: 1) an interest in MitS as an innovative navigation display, 2) challenges with identifying turns and orienting, 3) learning MitS over time, 4) the position of MitS in the field of view, 5) customizability and flexibility and 6) ) use in the context of a military operation. We discuss these themes and highlight areas for design improvements.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".