Integrated Time-Resolved Fluorescence and Diffuse Reflectance Spectroscopy Instrument for Intraoperative Detection of Brain Tumor Margin
Bibliographic record
Abstract
Time-resolved fluorescence (TRF) and diffuse reflectance (DR) spectroscopy are two optical biopsy modalities that have been studied in tumor diagnosis. Combination of TRF and DR spectroscopy allows us to obtain more features such as fluorescence intensity, lifetime, and optical properties; thus, potentially improving the tissue diagnostic accuracy. In this paper, an integrated TRF-DR spectroscopy instrument was developed to acquire TRF spectra as well as spatially resolved diffuse reflectance spectra in sequence for intraoperative detection of brain tumor margin. The performance of TRF-DR spectroscopy instrumentation was calibrated and evaluated using endogenous biomolecules, tissue phantoms, and ex vivo brain tumor specimens. The results demonstrated that the TRF-DR system is capable to retrieve the fluorescence and optical properties accurately.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".