Image processing for colour blindness correction
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
Colour blindness is a genetic mutation that alters the colour vision of the subjects by decreasing the sensitivity to certain colour wavelengths, depending on the defect. There are many forms of colour blindness ranging from monochromacy (black-white) to the most common form, the ¿red-green¿ variation where reds or greens are weakened, the vibrant shades are easily seen and the dull shades are difficult to perceive. A filter was designed based on the Ishihara colour tests in order to correct the colour blind deficiencies. This was successful for seeing the hidden objects within the test plates but did not translate well for real world images. The filter was modified, removing the dullest/lightest shades and shifting all the shades to the darker vibrant shades. The original image was shown to colour blind and normal vision subjects with results varying among all the subjects. After the modified filter was applied to a natural image, the colour blind and normal vision subjects were all able to correctly identify the test colours.
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