Monte Carlo calculated absorbed‐dose energy dependence of EBT and EBT2 film
Bibliographic record
Abstract
PURPOSE: The absorbed-dose energy dependence of GAFCHROMIC EBT and EBT2 film irradiated in photon beams is studied to understand the shape of the curves and the physics behind them. METHODS: The absorbed-dose energy dependence is calculated using the EGSnrc-based EGS_chamber and DOSRZnrc codes by calculating the ratio of dose to water to dose to active film layers at photon energies ranging from 3 keV to 18 MeV. These data are compared to the mass energy absorption coefficient ratios and the restricted stopping power ratios of water to active film materials as well as to previous experimental results. RESULTS: In the photon energy range of 100 keV to 18 MeV the absorbed-dose energy dependence is found to be energy independent within +/- 0.6%. However, below 100 keV, the absorbed-dose energy dependence of EBT varies by approximately 10% due to changes in mass energy absorption coefficient ratios of water to film materials, as well as an increase in the number of electrons being created and scattered in the central surface layer of the film. Results are found to disagree with previous experimental studies suggesting the possibility of an intrinsic energy dependence at lower photon energies. For EBT2 film the absorbed-dose energy dependence at low photon energies varies by 50% or 10% depending on the manufacturing lot due to changes in the ratio of mass energy absorption coefficients of the active emulsion layers to water. CONCLUSIONS: Caution is recommended when using GAFCHROMIC EBT/EBT2 films at photon energies below 100 keV. It is recommended that the effective atomic number of future films be produced as close to that of water and that thicker active layers are advantageous.
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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) | 0.004 | 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".