HybridPointing for Touch
Bibliographic record
Abstract
We propose CursorTap, an extension of Forlines et al.'s mixed, absolute and relative "HybridPointing" to large wall-sized multitouch displays. Our technique uses a relative pointing quasimode activated with one hand, while the other hand controls a distant cursor similar to a large touchpad. A controlled experiment compares the technique to standard absolute touch input as a baseline and a whole-display "Drag" technique representing a common alternate approach. Results show CursorTap is fastest for the common usage scenario of reaching distant targets and then returning to nearby targets. Overall, median selection times across distances are similar with CursorTap, but linearly increase with the other techniques. As further validation, a second study explore show people use CursorTap in a two-person game. The results found just over half of the participants choose to use CursorTap for half of the primary interactions where "enemies" are eliminated using a tap, drag, or lasso "tool".
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".