Modeling of fiber-optic fluorescence probes for strongly absorbing samples
Bibliographic record
Abstract
The dynamic range of fiber-optic fluorescent probes such as single fibers and fiber bundles is calculated for strongly absorbing samples, such as process liquids, foodstuffs, and lubricants. The model assumes an excitation beam profile based on a Lambertian light source and uses analytical forms of the collection efficiency, followed by an Abel transformation and numerical integration. It is found that the effect of primary absorption of the excitation light and secondary absorption of the fluorescence is profound. For fiber bundles and bifurcated fiber probes, the upper accessible concentration limit is roughly given by the absorption length of the primary and secondary absorption. Fluorescence detectors that are placed at right angles to the excitation beam axis or collinear to the beam axis are equally strongly affected by secondary absorption. A probe in which the same fiber is used for excitation and for collection of the fluorescence emerges as the fiber probe with the largest accessible concentration range.
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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".