Physical wedge as a tool for radiochromic film calibration
Bibliographic record
Abstract
Reliable calibration is one of the major challenges in using radiochromic films (RCF) for radiation dosimetry. In this study the feasibility of using dose gradients produced by a physical wedge (PW) for RCF calibration was investigated. The aim was to establish an efficient and reproducible method for calibrating RCF using a PW. Film strips were used to capture the wedge dose profile for five different exposures and the acquired scans were processed to generate corresponding net optical density wedge profiles. The proposed method was compared to the benchmark calibration, following the guidelines for precise calibration using uniform dose fields. The results of the benchmark comparison presented in this paper showed that using a single film strip for measuring wedge dose profile is sufficient for estimating a reliable calibration curve within the recorded dose range. Furthermore, the PW calibration can be extrapolated or extended by using multiple gradients for the optimal coverage of the desired calibration dose range. The method outlined in this paper can be readily replicated using the equipment and expertise commonly found in a radiotherapy center. Once the dose profile and central axis attenuation coefficient of the PW are determined, they can serve as a reference for a variety of calibrations using different types and batches of film. This investigation demonstrated that the calibration curves obtained with the presented PW calibration method are within the bounds of the measurement uncertainty evaluated for the conventional uniform dose field calibration method.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".