LensMouse
Bibliographic record
Abstract
We introduce LensMouse, a novel device that embeds a touch-screen display -- or tangible 'lens' -- onto a mouse. Users interact with the display of the mouse using direct touch, whilst also performing regular cursor-based mouse interactions. We demonstrate some of the unique capabili-ties of such a device, in particular for interacting with auxil-iary windows, such as toolbars, palettes, pop-ups and dia-log-boxes. By migrating these windows onto LensMouse, challenges such as screen real-estate use and window man-agement can be alleviated. In a controlled experiment, we evaluate the effectiveness of LensMouse in reducing cursor movements for interacting with auxiliary windows. We also consider the concerns involving the view separation that results from introducing such a display-based device. Our results reveal that overall users are more effective with LenseMouse than with auxiliary application windows that are managed either in single or dual-monitor setups. We conclude by presenting other application scenarios that LensMouse could support.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.009 |
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".