Design criteria for microstructured-optical-fiber-based surface-plasmon-resonance sensors
Bibliographic record
Abstract
Design strategies for microstructured-optical-fiber (MOF-) based surface-plasmon-resonance (SPR) sensors are presented. In such sensors, plasmons on the inner surface of the large metallized channels containing analyte can be excited by a fundamental mode of a single-mode microstructured fiber. Phase matching between a plasmon and a core mode can be enforced by introducing air-filled microstructures into the fiber core. Particularly, in its simplest implementation, the effective refractive index of a fundamental mode can be lowered to match that of a plasmon by introducing a small central hole into the fiber core. Resolution of the MOF-based sensors is demonstrated to be as low as 3×10−5 RIU, where RIU means refractive index unit. The ability to integrate large-size microfluidic channels for efficient analyte flow together with a single-mode waveguide of designable modal refractive index is attractive for the development of integrated highly sensitive MOF-SPR sensors operating at any designable wavelength.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".