Gluey: Developing a Head-Worn Display Interface to Unify the Interaction Experience in Distributed Display Environments
Bibliographic record
Abstract
Distributed display environments (DDEs) allow use of various specialized devices but challenge designers to provide a clean flow of data across multiple displays. Upcoming consumer-ready head-worn displays (HWDs) can play a central role in unifying the interaction experience in such ecosystems. In this paper, we report on the design and development of Gluey, a user interface that acts as a 'glue' to facilitate seamless input transitions and data movement across displays. Based on requirements we refine for such an interface, Gluey leverages inherent headworn display attributes such as field-of-view tracking and an always-available canvas to redirect input and migrate content across multiple displays, while minimizing device switching costs. We implemented a functional prototype integrating Gluey's numerous interaction possibilities. From our experience in this integration and from user evaluation results, we identify the open challenges in using HWDs to unify the interaction experience in DDEs.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".