X link color blind: A systematic review of congenital color vision deficiency cognitively and neurologically
Bibliographic record
Abstract
Color vision deficiency (CVD) can affect people’s perception and limits what job they takes. In order to distinguish colors, different cones differ in spectral sensitivity to capture photons. Several genes (OPN1LW, OPN1MW, ATF6, CNGA3, CNGB3, GNAT2, PDE6H, and PDE6C) are responsible for color vision deficiency. Mutation in these genes can cause deficiency in cones, which will result in reduction in color vision sensitivity. Gene therapy that target these genes showed prominent results in augmenting color vision, yet such methods remain in development and not widely used as treatment. CIE diagram shows the gamut difference in color vision deficiency individuals, and predicts how would the world looks to them. According to reduction theory, the CVD patient would be biased toward the color based on their intact gamut. Compensation glasses showed improved performance in Ishihara’s test, however, other measuring method was not used, furthermore, it is effectiveness on other types of color blind remain unknown. Due to the effective recovery of gene therapy and compensation glasses, further study on such methods is recommended for better recovery in CVD patients.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".