Dynamic control of polarization mismatch and coma aberrations in rod-GRIN assemblies
Why this work is in the frame
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Bibliographic record
Abstract
We describe the use of stacked electrically tunable liquid crystal lenses (TLCLs), along with rod gradient index (GRIN) fixed focus lenses, for endoscopic applications. Architectural and driving conditions are found for the optimization of total aberrations of the assembly. Particular attention is devoted to the coma and polarization aberrations. The coma aberration is reduced by stacking two TLCLs with "opposed" pre-tilt angles (all molecules are in the same plane), and then two such doublets are used with cross oriented molecules (in perpendicular planes) to reduce the polarization dependence. The obtained adaptive rod-GRIN lens enables a focus scan over 80μm (with exceptionally low RMS aberrations ≤0.16μm), making possible the high-quality observation of neurons at various depths.
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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 it