MultiFingerBubble: A 3D Bubble Cursor Variation for Dense Environments
Why this work is in the frame
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Bibliographic record
Abstract
In this work, we propose MultiFingerBubble, a new variation of the 3D Bubble Cursor. The 3D Bubble Cursor is sensitive to distractors in dense environments: the volume selection resizes to snap-to nearby targets. To prevent the cursor to constantly re-snap to neighboring targets, MultiFingerBubble includes multiple targets in the volume selection, and hence increases the targets effective width. Each target in the volume selection is associated with a specific finger. Users can then select a target by flexing its corresponding finger. We report on a controlled in-lab experiment to explore various design options regarding the number of fingers to use, and the target-to-finger mapping and its visualization. Our study results suggest that MultiFingerBubble is best used with three fingers and colored lines to reveal the mapping between targets and fingers.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it