In-vivo human retina imaging with 5μm axial resolution, at 92000 A-scans/s with 1μm spectral domain OCT system
Bibliographic record
Abstract
We have outfitted a 1060nm Spectral Domain Optical Coherence Tomography system with a prototype, high speed infrared linear array camera and a custom spectrally reshaped superluminescent diode to achieve 5μm axial resolution at 91,911 A-scans/s image acquisition rate in-vivo in the human retina. 4dB loss of sensitivity was observed as a result of the reduced integration time (7μs) of the fast camera as compared to similar commercially available cameras with 14μs integration time and 47kHz readout rate. Fewer motion artefacts were observed in the retinal images acquired with the fast camera, while the higher axial resolution along with deeper penetration allowed for improved visualization of fine morphological details such as retinal and choroidal capillaries and the deep choroidal structure.
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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 | 0.000 | 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) | 0.003 | 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".