Bibliographic record
Abstract
Objective To investigate the origin of signals from scanning laser Doppler flowmetry (SLDF) and the influence of axial scan depth on the measurement of blood flow in the rat retina. Methods We performed SLDF in 5 adult Sprague-Dawley rats using a specially modified Heidelberg retina flowmeter. Axial scans were obtained from +2 diopters (D) to −3 D (in steps of 0.25 D) or from +1 D to −2 D (in steps of 0.125 D) relative to the retinal surface. Fluorescein isothiocyanate–dextran angiograms were obtained in whole-mounted retinas to visualize the angioarchitecture and identify measurement locations in the SLDF flow maps. Axial SLDF flow profiles were obtained in an artery, vein, arteriole, venule, and capillary bed using the mean blood flow values in 2 × 2–, 4 × 4–, and 10 × 10–pixel measurement windows. Results The SLDF images showed good correspondence with the angiograms and resolution to third-order arterioles and venules; however, neither the superficial nor deep capillary circulations were visualized. Flow was imaged from large choroidal vessels. Measured flow from capillaries was independent of depth and indistinguishable from background levels. Conclusion The technique of SLDF images blood flow in larger retinal vessels but not in capillaries. Clinical Relevance Scanning laser Doppler flowmetry may not reliably measure capillary blood flow.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".