Superfine multiresonant fiber grating sensors assisted with silica capillaries
Bibliographic record
Abstract
We propose and demonstrate a superfine multiresonant fiber grating sensor characterized by superior spectral resolution and enhanced sensing capabilities. This sensor can be easily constructed by inserting a tilted fiber Bragg grating (TFBG) probe into a silica capillary filled with a refractive index (RI) matching oil. As the fiber cladding, the RI-matching oil, and the capillary all have the same RI, the cladding modes excited by the TFBG can extend into the RI-matching oil and capillary, facilitating surface sensing outside the capillary. Our study shows that the number of cladding modes increases, and the resonance spectrum becomes denser as the outer diameter of the capillary gets larger. As a result, the detection accuracy of RI based on mode cutoff wavelength identification can be improved. Particularly, with a capillary diameter of 1 mm, the heightened spectral density enhances refractometric accuracy by nearly an order of magnitude compared to the intrinsic TFBG. The superfine multiresonant fiber grating sensor proposed here is flexible in configuration and easy to fabricate, providing a new strategy for developing new fiber sensing devices.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".