Optimal Optical Coherence Tomography–Based Measures in the Diagnosis of Clinically Significant Macular Edema
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To compare optical coherence tomography-based measures of retinal thickness and volume as quantitative tests for clinically significant macular edema (CSME). DESIGN: Diagnostic validation study. METHODS: Sixty-five eyes with diabetic retinopathy underwent stereo photographic and optical coherence tomographic examination. Stereo photographs were examined in a masked fashion to determine the presence or absence of CSME according to criteria from the Early Treatment Diabetic Retinopathy Study. Optical coherence tomography-based measurements of central foveal thickness as well as retinal volumes within a series of radii of fixation were generated. The main outcome measures were areas under receiver operating characteristic curves. Likelihood ratios, sensitivities, and specificities for the diagnosis of CSME were also evaluated. RESULTS: Retinal volumes within radii of 0.50 mm and 1.11 mm of fixation and central foveal thickness were the best variables for discriminating between those with and without CSME as evidenced by analysis of receiver operating characteristic curves. There were no significant differences among these 3 variables in their performance as diagnostic tests for CSME. CONCLUSIONS: Optical coherence tomography-based retinal volume and central foveal thickness variables display comparable abilities to discriminate between those with and without CSME. Both measures may have clinical applications as quantitative diagnostic tests for CSME.
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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 | 0.001 |
| 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