Towards optimum sample-probe-spectrometer system design by adjusting receiving fiber end face position and probe-membrane sample separation
Bibliographic record
Abstract
A two-fiber probe interrogated by a spectrometer for the measurement of fluorescence emitted from a thin layer of membrane is investigated. For a specific spectrometer, an optimum fiber probe design exists to maximize the sample-probe-spectrometer system performance. In this paper, for the first time, we report that by separating the front end faces of the receiving and illuminating fibers, spectrum resolution and fluorescence collection capability may be simultaneously enhanced. Theoretical and experimental results reveal that such an optimized system collects more emitted rays with incident angles that fall within the full acceptance angle of the slit. The relative collection efficiency increases to 63% when the membrane is positioned very close to the probe tip. By adjusting positions of the receiving fiber and the membrane sample to an optimized combination, we also prove that the optimum performance of spectrometer can be achieved.
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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 | 0.001 |
| 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".