Why higher resolution graphics cards are needed in colour vision research
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
Abstract The colour resolution of a 14‐bit and an 8‐bit per channel graphics card were evaluated and compared with the just noticeable difference between colours (varying only in luminance) for: (1) a standard observer (based on the CIE 1976 L * u * v * colour space) and (2) real observers in a colour discrimination task. The results of this study show that an 8‐bit per channel graphics card seems adequate for colour discrimination experiments where stimuli only vary in luminance. However, considering that the resolution of the graphics card should be equal to the Nyquist rate, an 8‐bit per channel card turns out to be inadequate. For colour discrimination experiments where stimuli only vary in chromaticity, there is an undersampling of the colour space with respect to MacAdam ellipses when using 8‐bit per channel graphics cards. The extremely fine colour resolution of a 14‐bit per channel graphics card overcomes these problems. Its use allows more accurate measurements of achromatic and chromatic discrimination thresholds and avoids experimental (spatial or luminance) artefacts, such as bandings that can occur on achromatic or chromatic gradients. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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