Fabrication of Multiple Superimposed Fiber Bragg Gratings for Multiple Parameter Sensing
Classification
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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Multiple superimposed fiber Bragg gratings (FBGs) are fabricated based on a non-uniform single-core As2Se3-Poly methyl methacrylate (PMMA) tapered fiber, by which superimposition of up to nine chirped FBGs is achieved. Multiple superimposed uniform FBGs are first inscribed on the nonuniform waveguide and multiple superimposed chirped FBGs are obtained by stretching the non-uniform waveguide. Simultaneous measurement of temperature and strain is realized based on two superimposed chirped FBGs at wavelengths of 1540 nm (FBG1) and 1550 nm (FBG2), respectively. The central wavelength shifts and bandwidth changes of the two superimposed chirped FBGs, when temperature and strain change, are measured, respectively. Four matrices are defined to predict the temperature and strain change, and the one defined by measuring the bandwidth change of FBG1 and the central wavelength shift of FBG2 gives the most accurate measurement with the sensitivities of 29.1 pm/°C for temperature measurement and 0.373 pm/με for strain measurement by measuring the bandwidth change of FBG1, and 75.1pm/°C for temperature measurement and 0.245 pm/με for strain measurement by measuring the central wavelength shift of FBG2, respectively. The resolutions for temperature and strain measurement are enhanced by more than a factor of 10, respectively, compared with those using the matrix defined by measuring the wavelength shifts of FBG1 and FBG2. A large strain change from 0 to 22000 με is achieved due to the low stiffness of As2Se3-PMMA taper, which is far beyond the operating range of silica materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it