Estimation of hue discrimination thresholds using a computer interactive method
Bibliographic record
Abstract
Abstract An experimental approach is described for measuring colour discrimination thresholds of human observers. Special software was developed for the accurate display of colour pairs on a high resolution CRT, using serial feedback from a spectroradiometer. Discrimination thresholds between a test and a target colour are determined by repeatedly showing an observer a circle composed of four separate quadrants, one of which has a different colour from the other three. Three quadrants are of the test colour and one of the target colour, or vice versa. Observers are asked to select the quadrant that differs from the others. An experiment is described where hue‐dependent effects affecting hue discrimination are investigated. Eighteen hue threshold values around the hue circle, at constant L = 51 and C = 25, were measured for three observers. Hue thresholds were found to vary around the hue circle, exhibiting an abrupt change in the blue to purple region (240° ≤ hab,10 = 300°) This change is not fully accounted for by any CIELAB‐based colour difference formula, including the most recent CIEDE2000 formula. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 410–415, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20153
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".