Volumetric directional optical coherence tomography
Bibliographic record
Abstract
Photoreceptor loss and resultant thinning of the outer nuclear layer (ONL) is an important pathological feature of retinal degenerations and may serve as a useful imaging biomarker for age-related macular degeneration. However, the demarcation between the ONL and the adjacent Henle's fiber layer (HFL) is difficult to visualize with standard optical coherence tomography (OCT). A dedicated OCT system that can precisely control and continuously and synchronously update the imaging beam entry points during scanning has not been realized yet. In this paper, we introduce a novel imaging technology, Volumetric Directional OCT (VD-OCT), which can dynamically adjust the incident beam on the pupil without manual adjustment during a volumetric OCT scan. We also implement a customized spoke-circular scanning pattern to observe the appearance of HFL with sufficient optical contrast in continuous cross-sectional scans through the entire volume. The application of VD-OCT for retinal imaging to exploit directional reflectivity properties of tissue layers has the potential to allow for early identification of retinal diseases.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".