Using radiance predicted by the P3-approximation for treatment planning for PDT for prostatic carcinoma
Bibliographic record
Abstract
The P3-Approximation was used to optically characterize ex-vivo human prostate and to investigate the role that optical inhomogeneity, at the boundary between the prostate and its surrounding tissues, will play in tissue light dosimetry. Each prostate was found to be optically homogeneous, observing only slight variations in the scattering coefficient (o = 29 mm' to 34 mni'). Every prostate had the same absorption coefficients (o =0.08 mm') and anisotropy factors (g = 0.94). The variation in scattering coefficient had nearly inconsequential effects on theoretical fluence calculations, fluence being the key method of quantifying light for dosimetry purposes. To explore the boundary effects, a prostate was suspending above the bottom of a black painted bowl. Radiance measurements were taken and then intralipid was added until the prostate was completely submersed. The radiance measurements after the addition of intralipid varied greatly from the initial measurements without intralipid. An increase in light intensity was observed, as well as alteration in the shape of the radiance profile implying that surrounding tissues will have an effect on light transport. These must be characterized and integrated into a comprehensive light dosimetry model for PDT ofprostatic carcinoma.
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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 | 0.001 |
| 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".