The effect of image alignment on capillary blood flow measurement of the neuroretinal rim using the Heidelberg retina flowmeter
Bibliographic record
Abstract
AIM: To examine the influence of image alignment on the repeatability of blood flow measurements of the optic nerve. METHODS: 10 normal subjects were examined. Heidelberg retina tomograph imaging was performed to establish best location and focus for the temporal neuroretinal rim. Two high quality Heidelberg retina flowmeter (HRF) images were acquired for three methods of alignment: central, nasal, and temporal. A 10 x 10 pixel measurement window was selected and exactly reproduced on all images. The interquartile pixel values were used to calculate capillary flow. ANOVA, intraclass correlation coefficients (ICC) and the coefficient of repeatability (CoR) were used for analysis. RESULTS: There was no difference between methods (p = 0.47) or between visits (p = 0.51). The ICCs were 0.83 for the central, 0.34 for the nasal, and 0.42 for the temporal alignment. The CoR was 31.5 for central (mean effect 235.1), 234.6 for nasal, and 256.7 for temporal alignment. CONCLUSION: Central alignment was the most repeatable method for the measurement of neuroretinal rim capillary blood flow using the HRF.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".