Combined compression-tension strain sensor over 1 µε–20 mε by using non-uniform multiple-core-offset fiber
Bibliographic record
Abstract
Combined compression-tension strain sensors with a range of 1 micro to a maximum of 20 milli-strain based on non-uniform multiple-core-offset fibers have been realized. A large strain range with high resolution is ideal for monitoring deformation of steel structures where a large compressive and tensile strain co-exists. Thanks to core-offset splicing of non-uniform fiber segments, unique asymmetric waveguides reduce the degeneracy of each section, realizing a reflection spectrum with a large range and irregular shape. Furthermore, enhanced multi-mode interference induced from high-order modes in silica cladding and air results in the large strain range with high resolution in both compression and tension regions. The sensitivity of 7.93 pm/µ ε with a strain step of 1.7 µ ε is achieved for micro-strain measurement. For milli-strain measurement, a strain coefficient of 1.298 nm/m ε over a tensile strain of 13.2 m ε is realized; in the compressive strain case, a coefficient of − 1.251 n m / m ε over compression of 20.1 m ε is observed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".