Characterization of the modeled fluence distribution for non-ideal cylindrical diffusers in intraluminal and interstitial settings
Bibliographic record
Abstract
The effect of non-ideal cylindrical diffusers on the fluence rate distribution is studied in intraluminal and interstitial light delivery settings. Two types of diffuser non-uniformities are modeled: a forward-directed polar emission profile, and a longitudinal emission profile with a peak at the distal tip of the diffuser. These effects were compared with an ideal diffuser constructed via a superposition of isotropic point sources placed along the length of the diffuser. Monte Carlo simulations were run for a wide range of optical properties and the resulting fluence rate distribution were analyzed. Parameters describing the shape of these distributions were defined. The longitudinal profile most strongly influenced the shape of the fluence rate distribution displaying high local fluence rates, high degrees of asymmetry, and deeper penetration into tissue. These characteristics are particularly evident for interstitial illumination. In intraluminal illumination, both non-ideal profiles produced a shift of the fluence rate, but, while remaining largely insensitive to optical properties for the longitudinal diffuser, the position of the peak fluence rate varied to a considerable extent for the polar anisotropic diffuser, particularly as a function of albedo. Measurement of the polar emission profile and its inclusion in treatment planning, based on the tissue optical properties, is recommended for the intraluminal geometry. The longitudinal emission profile should be determined regardless of the application, together with knowledge of the tissue optical properties.
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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 | 0.001 | 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".