Smartwatches + Head-Worn Displays: the "New" Smartphone
Bibliographic record
Abstract
We are exploring whether two currently mass marketed wearable devices, the smartwatch (SW) and head-worn displays (HWDs) can replace and go beyond the capabilities of the mobile smartphone. While smartphones have become indispensable in our everyday activities, they do not possess the same level of integration that wearable devices afford. To explore the question of whether and how smartphones can be replaced with a new form factor, we present methods for considering how best to resolve the limited input and display capabilities of wearables to achieve this vision. These devices are currently designed in isolation of on another and it is as yet unclear how multiple devices will coexist in a wearable ecosystem. We discuss how this union addresses the limitations of each device, by expanding the available interaction space, increasing availability of information and mitigating occlusion. We propose a design space for joint interactions and illustrate it with several techniques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.017 | 0.028 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".