Tuning the sensing responses of polymer-coated fiber Bragg gratings
Bibliographic record
Abstract
We demonstrate the application of polyimide-coated fiber Bragg grating (FBG) as a substance sensor and reveal the dependences of the sensitivity and time response on the coating thickness as well as factors influencing these properties. As an example of polyimide-coated sensor for detecting soluble substances, the use of the grating for salinity measurement shows that a judicious selection of coating thickness is needed in order to achieve suitable sensitivity and time response for specific application. The experimental results indicated that the salinity sensitivities of the polyimide-coated FBGs with coating thicknesses of 11, 17, 20, and 24 μm were 1.45, 2.45, 2.95, and 3.70 pm/% (blueshifted), respectively. In addition, the response time is another signature for discriminating different parameters.
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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 | 0.000 | 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) | 0.000 | 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".