Predictive interaction using the delphian desktop
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper details the design and evaluation of the Delphian Desktop, a mechanism for online spatial prediction of cursor movements in a Windows-Icons-Menus-Pointers (WIMP) environment. Interaction with WIMP-based interfaces often becomes a spatially challenging task when the physical interaction mediators are the common mouse and a high resolution, physically large display screen. These spatial challenges are especially evident in overly crowded Windows desktops. The Delphian Desktop integrates simple yet effective predictive spatial tracking and selection paradigms into ordinary WIMP environments in order to simplify and ease pointing tasks. Predictions are calculated by tracking cursor movements and estimating spatial intentions using a computationally inexpensive online algorithm based on estimating the movement direction and peak velocity. In testing the Delphian Desktop effectively shortened pointing time to faraway icons, and reduced the overall physical distance the mouse (and user hand) had to mechanically traverse.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it