Gaze-contingent depth of field in realistic scenes
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
Computer-generated objects presented on a display typically have the same focal distance regardless of the monocular and binocular depth cues used to portray a 3D scene. This is because they are presented on a flat screen display that has a fixed physical location. In a stereoscopic 3D display, accommodation (focus) of the eyes should always be at the distance of the screen for clear vision regardless of the depth portrayed; this fixed accommodation conflicts with vergence eye movements that the user must make to fuse stimuli located off the screen. This is known as accommodation-vergence conflict and is detrimental for user experience of stereoscopic virtual environments (VE), as it can cause visual discomfort and diplopia during use of a stereoscopic display. It is believed that, by artificially simulating focal blur and natural accommodation, it is possible to compensate for the vergence-accommodation conflict and alleviate these symptoms. We hypothesized that it is possible to compensate for conflict with a fixed accommodation cue by adding simulated focal blur according to instantaneous fixation.
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