Extraneous factors affecting retinal oximetry
Bibliographic record
Abstract
Abstract Purpose To identify extraneous factors that can impact the outcome of retinal oximetry calculations and to discuss how these factors might be negated. Methods 1. Empiric observation of extraneous factors suspected to impact the outcome of retinal oximetry. 2. Controlled studies of established and suspected extraneous factors. Results 1. The repeatability of a manual oximetry technique was found to be good. The standard deviations of Optical Density (OD) values ranged from 0.01 to 0.06 OD units and from 0.01 to 0.07 OD units for first degree arterioles and venules, respectively. The Co‐efficient of Repeatability (CoR) ranged from 0.02 to 0.11 OD units (relative to a mean OD of 0.15 [0.06‐0.23] OD units) for arterioles and 0.03 to 0.14 OD units (relative to a mean OD of 0.25 [0.17‐0.31] OD units) for venules. Good reliability (p<0.001) was found for arterioles and venules. 2. Dual ratiometric calculations of retinal oxygen saturation (SO2) demonstrated a significant decrease of arterial SO2 during hypoxia. 3. The order of acquisition of spectral images did not influence the outcome of retinal oximetry results. 4. The manual calculation of SO2 values from reflectance data was significantly influenced by the selected retinal locations within and either side of a given retinal vessel. Other extraneous factors included: 5. Variation in retinal pigmentation; 6. Density of retinal pigmentation); 7. Instrument flash intensity; 8. Lenticular irregularities; 9. Tear film irregularities. Conclusion Although the assessment of retinal SO2 in ocular diseases would seem to be of clinical value, a number of extraneous factors must first be taken into account to avoid erroneous conclusions. Commercial interest
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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 | 0.026 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".