Multi-modal functional sensorless adaptive optics for small animal retinal imaging
Bibliographic record
Abstract
The proposed preclinical study investigates pathological characteristics of retinal diseases such as Age-related Macular Degeneration (AMD) with transgenic small animal models using a multi-modal functional small animal retinal imaging system. For characterizing the animal models, we visualize the melanin concentration, lipofuscin accumulation, and choriocapillaris using a single imaging system. The system implements Polarization-Sensitive Optical Coherence Tomography (PS-OCT), fluorescence Scanning Laser Ophthalmoscope (fSLO), and Sensorless Adaptive Optics (SAO) for the visualizations of pathological features. As preliminary data, we acquired three different mice models and visualized the outer retinal thickness and melanin concentration. The newly developing system is expected to provide multilateral perspectives for further studies in AMD, enabling vision scientists to investigate the correlations between melanin, lipofuscin, and choriocapillaris for the root cause of AMD.
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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 | 0.000 | 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 | 0.000 |
| 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 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".