Poster — Thur Eve — 28: Feasibility Study for Open Door Low Energy Treatments Using Maze‐Type Bunkers Designed for Dual Energy Linacs
Bibliographic record
Abstract
Older bunkers designed for dual energy linacs were often constructed with both a maze and high energy door. The door provides both radiation safety and access control, however, it may be desirable to limit use of the high energy door to reduce mechanical wear and improve workflow. We conducted a feasibility study to determine if our high energy linac (Varian 21EX with electrons and 6/18 MV photons) located in a bunker with a maze and high energy door could be operated with the door closed for 18 MV beams only. Dose estimation using NCRP‐151, followed by measurement with TLD and survey meters was carried out. Workload and use factors from literature, and from realistic data derived from our ARIA database were used. NCRP‐151 calculations underestimated the measured value, and this discrepancy became worse for points further into the maze. For our workload of 7 000 Gy m2/year an equal gantry angle distribution suggests 1.0 mSv extra per year, while a realistic workload and use factor derived from our database suggests 0.1 mSv extra per year for the 6 MV door‐open scenario. A door occupancy factor of 0.125 further reduces these estimates. The worst case In‐Any‐One‐Hour Time Averaged Dose‐Equivalent Rate was determined to be 0.84 mSv/hr. A Last‐Person‐Out system linked to a light guard in parallel with a energy‐select logic system was bench tested. Adapting existing high energy bunkers designed with maze and door for operation with the door closed for high energy photon beams only is a viable option.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".