Development and characterization of multi-sensory fluence rate probes
Bibliographic record
Abstract
Multi-sensory fluence rate probes (MSPs) yield several simultaneous measurements of photodynamic therapy (PDT) treatment light fluence from a single interstitial probe. Fluorescent sensors are embedded at desired positions along the axis of the optical fibre. A single fluorescence emission spectrum is obtained and decomposed using a partial least squares (PLS)-based analysis to yield the fluence at each sensor's location. The responsivity, linearity and possible photodegradation of each fluorophore chosen for the MSPs were evaluated using single-sensor probes. The performance of two- and three-sensor MSPs was evaluated experimentally. Individual fluorescence spectra collected from each sensor on the MSP were used to construct the training set necessary for the PLS-based analysis. The MSPs' responsivity, spatial resolution and accuracy were evaluated relative to a single scattering-tip detector. Three-fluorophore MSPs permitted three simultaneous measurements of the fluence rate gradient in a tissue-like phantom, with an average accuracy of 6.7%. No appreciable photodegradation or cross-talk was 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 | 0.001 | 0.002 |
| 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".