Advanced capabilities of the multimodal adaptive optics imager
Bibliographic record
Abstract
We recently developed several versions of a multimodal adaptive optics (AO) retinal imager, which includes highresolution scanning laser ophthalmoscopy (SLO) and Fourier domain optical coherence tomography (FDOCT) imaging channels as well as an auxiliary wide-field line scanning ophthalmoscope (LSO). Some versions have also been equipped with a fluorescence channel and a retinal tracker. We describe the performance of three key features of the multimodal AO system including: simultaneous SLO/OCT imaging, which allows SLO/OCT co-registration; a small animal imaging port, which adjusts the beam diameter at the pupil from 7.5 to 2.5 mm for use with small animals ubiquitous in biological research or for extended depth-of-focus imaging in humans; and slow scan Doppler flowmetry imaging using the wide field auxiliary LSO imaging channel. The systems are currently deployed in several ophthalmology clinics and research laboratories and several investigations have commenced on patients with a variety of retinal diseases and animals in vision research.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".