Feasibility of interstitial near-infrared radiance spectroscopy platform for<i>ex vivo</i>canine prostate studies: optical properties extraction, hemoglobin and water concentration, and gold nanoparticles detection
Bibliographic record
Abstract
The canine prostate is a close match for the human prostate and is used in research of prostate cancers. Determining accurately optical absorption and scattering properties of the gland in a wide spectral range (preferably in a minimally invasive way), linking optical properties to concentrations of major endogenous chromophores, and detecting the presence of localized optical inhomogeneities like inclusions of gold nanoparticles for therapeutic and diagnostic purposes, are among the major challenges for researchers. The goal of the article is to demonstrate a feasibility of the multifunctional radiance spectroscopy platform in providing the required information. For ex vivo canine prostate, extraction of the effective attenuation and diffusion coefficients using relative cw radiance measurements was demonstrated in the 650- to 900-nm range. The derived absorption coefficient was decomposed to contributions from 9.0 μM HbO₂, 29.6 μM Hb, and 0.47 fractional volume of H₂O. Detection of a localized inclusion containing ∼1.5·1010 gold nanorods (0.8 μg Au) at 10 mm distance from the urethra was achieved with the detector in the urethra and the light source in a virtual rectum position. The platform offers the framework for a systematic study of various chromophores in the prostate that can be used as comprehensive diagnostic markers.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".