Are neutrons responsible for the dose discrepancies between Monte Carlo calculations and measurements in the build-up region for a high-energy photon beam?
Bibliographic record
Abstract
This study presents measured neutron dose using a neutron dosimeter in a water phantom and investigates a hypothesis that neutrons in a high-energy photon beam may be responsible for the reported significant dose discrepancies between Monte Carlo calculations and measurements at the build-up region in large fields. Borated polyethylene slabs were inserted between the accelerator head and the phantom in order to remove neutrons generated in the accelerator head. The thickness of the slab ranged from 2.5 cm to 10 cm. A lead slab of 3 mm thickness was also used in the study. The superheated drop neutron dosimeter was used to measure the depth-dose curve of neutrons in a high-energy photon beam and to verify the effectiveness of the slab to remove these neutrons. Total dose measurements were performed in water using a WELLHOFER WP700 beam scanner with an IC-10 ionization chamber. The Monte Carlo code BEAM was used to simulate an 18 MV photon beam from a Varian Clinac-2100EX accelerator. Both EGS4/DOSXYZ and EGSnrc/DOSRZnrc were used in the dose calculations. Measured neutron dose equivalents as a function of depth per unit total dose in water were presented for 10 x 10 and 40 x 40 cm2 fields. The measured results have shown that a 5-10 cm thick borated polyethylene slab can reduce the neutron dose by a factor of 2 when inserted between the accelerator head and the detector. In all cases the measured neutron dose equivalent was less than 0.5% of the photon dose. In order to study if the ion chamber was highly sensitive to the neutron dose, we have investigated the disagreement between the Monte Carlo calculated and measured central-axis depth-dose curves in the build-up region when different shielding materials were used. The result indicated that the IC-10 chamber was not highly sensitive to the neutron dose. Therefore, neutrons present in a high-energy photon beam were unlikely to be responsible for the reported discrepancies in the build-up region for large 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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".