Luminance calibration of virtual reality displays in Unity
Bibliographic record
Abstract
Virtual reality (VR) displays are an increasingly popular medium for experiments on visual perception. This presents the challenge of showing precisely controlled stimuli on devices that were not primarily designed for research. Here we describe methods for controlling stimulus luminance in VR experiments created in Unity using the Built-in Render Pipeline. We discuss the Gamma/Linear setting, measuring luminance in a VR headset, and using color grading in Unity's Post-Processing Stack to make stimulus luminance proportional to achromatic RGB value. We provide MATLAB code that uses luminance measurements from a VR headset to generate the lookup table that Unity requires for linearizing luminance. We emphasize that when creating experiments in this complex environment, it is important to experiment with the rendering process to confirm that stimuli are displayed as expected. We show results of several such tests and provide code as a starting point for readers who wish to run further tests related to their own research.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".