Bibliographic record
Abstract
We present HoloFlex, a 3D flexible smartphone featuring a light-field display consisting of a high-resolution P-OLED display and an array of 16,640 microlenses. HoloFlex allows mobile users to interact with 3D images featuring natural visual cues such as motion parallax and stereoscopy without glasses or head tracking. Its flexibility allows the use of bend input for interacting with 3D objects along the z axis. Images are rendered into 12-pixel wide circular blocks-pinhole views of the 3D scene-which enable ~80 unique viewports at an effective resolution of 160 × 104. The microlens array distributes each pixel from the display in a direction that preserves the angular information of light rays in the 3D scene. We present a preliminary study evaluating the effect of bend input vs. a vertical touch screen slider on 3D docking performance. Results indicate that bend input significantly improves movement time in this task. We also present 3D applications including a 3D editor, a 3D Angry Birds game and a 3D teleconferencing system that utilize bend input.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.117 | 0.034 |
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".