3D tomodosimetry using scintillating fibers: proof-of-concept
Bibliographic record
Abstract
We present a novel, high-resolution 3D dosimeter based on the tomographic acquisition of the dose using long scintillating fibers. This study aims to demonstrate the concept of the dosimeter with simulated acquisitions using the input dose from Pinnacle 3 . The dosimeter is composed of concentric, cylindrical planes in which scintillating fibers are placed at different angles between the fiber and the cylindrical plane. Upon a complete rotation of the device around its central axis, the incident dose distribution on the cylindrical planes can be reconstructed using tomographic reconstruction algorithm. The 3D dose in the dosimeter can then be interpolated from the cylindrical 2D dose distributions. Using a simulated acquisition composed of two concentric cylindrical planes of 36 and 32 fibers each, we achieve below 1% local dose difference between the reconstructed 3D dose and the expected dose from Pinnacle 3 in the high dose, low gradient region of the volume encompassed inside the innermost cylindrical plane. The results show the potential of the method to perform high-resolution 3D dose measurements of both square and IMRT fields.
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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) | 0.000 | 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 | 0.000 |
| 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".