Simulation and experimental detection of radiation-induced acoustic waves from a radiotherapy linear accelerator
Bibliographic record
Abstract
Acoustic waves are generated in objects irradiated with megavoltage photon beams produced by a clinical linear accelerator. The detection of such induced acoustic waves (IAWs) has potential applications in radiation therapy dosimetry. This work developed a novel simulation platform to model IAWs by combining radiotherapy Monte Carlo and acoustic wave transport simulation techniques. Simulations and experimental measurements were performed to assess the IAWs when a lead block suspended in a water tank was irradiated with a photon beam produced by a clinical linear accelerator. Simulations correctly predicted the frequency of such IAWs, which allowed improved experimental detection through the development of a custom band-pass filter and signal amplification system. Photon beam energy, lead block depth, and lead block distance from the transducer were varied, and experimental and simulated signals showed the same trends for such set-up changes. These results demonstrate the ability of our simulation platform to accurately predict the frequency spectrum and relative amplitude trends of IAWs. The simulation platform can be applied to assess IAWs in clinically relevant radiotherapy dosimetry situations.
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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 | 0.001 | 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".