Rugate filters grown by Glancing Angle Deposition
Bibliographic record
Abstract
Recent progress in thin film optical coating technology has enabled more complex filter designs and better control of out of band interference. One of the most significant advances in optical filters has been the manufacture of rugate filter designs based on sinusoidal variation of refractive index. The realization of a rugate filter requires a means of depositing an optical material whose refractive index can be significantly varied over a wide range, while having precise control of the index. The Glancing Angle Deposition (GLAD) technique satisfies these requirements by allowing fabrication of films with nano-engineered morphology whose optical properties can be tailored. GLAD is based on thin film physical vapor deposition by evaporation and employs oblique angle flux and substrate motion to allow nanometer scale control of structure and optical properties. Silicon rugate filter prototypes were made according to design specifications using computer control of deposition parameters which influence the film optical response.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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".