The study of extraneous conditions that affect tilt-based pointer movements
Bibliographic record
Abstract
Introduction: With the rapid evolution of mobile devices, there is also a tremendous growth in their applications. This triggers new research on more efficient techniques of humancomputer interaction. To point at an object of interest seen on the screen of a mobile device, various new methods were suggested recently. Methods: This paper presents the results of a user study that employed tilting as a technique for entering text. The independent variables in the user study were mobility (sitting, walking, sitting in the moving bus) and keyboard size (5×3, 10×4). The experiment involved 50 participants aged from 22 to 65. Results: In the walking condition, it took on average 11.3% more time for participants to complete the task compared to the sitting condition with 5×3 keyboard, and 45.1% more time compared to the sitting condition with 10×4 keyboard. Keyboard size had a marked influence on task completion time. In addition, task completion time while traveling by bus was 3.2% longer than that observed for the walking condition with 5×3 keyboard. Surprisingly, task completion time with 10×4 keyboard while traveling by bus was 10.4% shorter compared to the walking condition. Error rate and movement efficiency were investigated additionally to find out the explanation for such performance data.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".