Digital photographic screening for diabetic retinopathy in the James Bay Cree
Bibliographic record
Abstract
This study evaluates a single, 45-degree fundus image from a non-mydriatic camera for the triage of subjects at risk for diabetic retinopathy. A complete retinal assessment by a retina specialist was the main comparator for the camera. Inter-observer agreements were calculated for the reading of digital images with different grades of retinopathy. Two hundred eyes of 100 consecutive subjects were evaluated as part of the James Bay diabetic retinopathy screening project; 62% of subjects had no retinopathy, 12% had microaneurysms only, 24% had non-proliferative retinopathy, 5% had clinically significant macular edema (CSME), and 2% had proliferative disease (PDR). The Kappa statistic for two independent observers was 0.85 (p < 0.001) for the identification of retinopathy from the digital images. The sensitivity of the digital camera for the evaluation of any retinopathy was 84.4%, for CSME and/or PDR it was over 90%. The use of a single digital retinal image for the evaluation of diabetic retinopathy was performed with a high degree of inter-observer concordance and a high degree of sensitivity.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".