Optical fibre Bragg grating cladding mode sensors
Bibliographic record
Abstract
In this paper we propose and demonstrate two forms of a device for sensing cladding modes efficiently. The cladding modes, generated by an untilted and tilted fibre Bragg grating (TFBG) written in SMF28 fibre are captured by splicing it to an in-line double-clad fibre coupler (DCFC). A comaprison is made of the capture efficiency of the cladding modes in two configurations; one in which the TFBG is taper spliced to the DCF, or in the other in which an FBG in an SMF28 is etched down to match the outer core of the DCF. In both cases the cladding modes are captured efficiently, but with significantly improved results for the former configuration. We demonstrate surrounding refractive index sensing using a new signal analysis scheme based on the extinction of each cladding mode resolved over a bandwidth of over ~60nm. This robust device has the advantage of faithfully transmitting the cladding modes over a long distance and is therefore suitable for remote sensing over long distances. The sensitivity of the device is discussed. This device may be used in a variety of applications such as for bend, strain, temperature and surrounding refractive index sensing.
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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) | 0.000 | 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 | 0.001 | 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".