Enhanced novel fiber-optic sensor for efficient fluorescence collection
Bibliographic record
Abstract
In this article the enhancement of the novel fiber-optic fluorescent sensor is demonstrated. The novel sensor that was developed by our group is based on the collection of the fluorescence from the sidewall of the multimode optical fiber which is partly de-cladded and covered by the sample under the test (SUT). The most part of the fluorescent intensity is carried by the leaky rays which are inaccessible in traditional evanescent-wave fluorescence fiber sensors. In our previous structure, some part of a refracting power is collected in the de-cladded segment and used to excite the lower order lossless modes in the cladded part by an end-face mode-mixer. In the enhanced type of our sensor we discovered that the mode-mixer on the side-wall, rather than on the end-face, is more efficient. The fluorescence efficiency increased in this type of enhanced sensor by about 88%. Moreover, the capability of multiplexing of the different SUT on one fiber is a promising advantage of this architecture with a view to develop the multi-channel chemical detection system with inexpensive simple fiber-optic.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".