Military Research ColorDx and Printed Color Vision Tests
Bibliographic record
Abstract
PURPOSE: To determine the equivalence of the ColorDx Military Research version (mColorDx) test and three printed pseudoisochromatic tests (HRR, Ishihara, and PIPIC) for color vision testing. METHODS: Participating in the study were 75 color-normals and 47 subjects with red-green color vision defects. Color vision was classified by an anomaloscope. The HRR (4(th) edition), Ishihara 38-plate edition, and PIPIC tests are printed color vision tests, whereas mColorDx test figures were displayed on a calibrated computer desktop monitor. All tests were repeated in about 1 wk. RESULTS: The kappa level of agreement (κ) values with the anomaloscope for screening for each test was 0.96 or greater. The values were statistically identical. Specificity for each test was at least 0.99 and sensitivity was at least 0.95. The repeatability of the screening sections for all tests was very good with κ values greater than 0.95. Deutans tended to miss the tritan screening plates on the HRR and mColorDx tests. The Spearman rank correlation coefficients between the severity of the defect and anomaloscope range was moderate with r = 0.45 for the mColorDx and r = 0.6 for the HRR. Both the mColorDx and HRR had perfect agreement with the anomaloscope in classifying the defects as either protan or deutan. CONCLUSION: The validity of the four tests for color vision screening was statistically identical; however, the HRR may be preferred because it had the highest sensitivity of 0.99, a specificity of 1.0, and a reasonable correlation between the severity rating of the defect and the anomaloscope range.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".