Multi-parameter sensor based on random fiber lasers
Why this work is in the frame
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Bibliographic record
Abstract
We demonstrate a concept of utilizing random fiber lasers to achieve multi-parameter sensing. The proposed random fiber ring laser consists of an erbium-doped fiber as the gain medium and a random fiber grating as the feedback. The random feedback is effectively realized by a large number of reflections from around 50000 femtosecond laser induced refractive index modulation regions over a 10cm standard single mode fiber. Numerous polarization-dependent spectral filters are formed and superimposed to provide multiple lasing lines with high signal-to-noise ratio up to 40dB, which gives an access for a high-fidelity multi-parameter sensing scheme. The number of sensing parameters can be controlled by the number of the lasing lines via input polarizations and wavelength shifts of each peak can be explored for the simultaneous multi-parameter sensing with one sensing probe. In addition, the random grating induced coupling between core and cladding modes can be potentially used for liquid medical sample sensing in medical diagnostics, biology and remote sensing in hostile environments.
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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) | 0.001 | 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 it