Characteristics of induced activity from medical linear accelerators
Bibliographic record
Abstract
A study of the induced activity in a medical linear accelerator (linac) room was carried out on several linac installations. Higher beam energy, higher dose rate, and larger field size generally result in higher activation levels at a given point of interest, while the use of multileaf collimators (MLC) can also increase the activation level at the isocenter. Both theoretical and experimental studies reveal that the activation level in the morning before any clinical work increases from Monday to Saturday and then decreases during the weekend. This weekly activation picture keeps stable from one week to another during standard clinical operation of the linac. An effective half-life for a given point in the treatment room can be determined from the measured or calculated activity decay curves. The effective half-life for points inside the treatment field is longer than that for points outside of the field in the patient plane, while a larger field and longer irradiation time can also make the effective half-life longer. The activation level reaches its practical saturation value after a 30 min continuous irradiation, corresponding to 12 000 MU at a "dose rate" of 400 MU/min. A "dose" of 300 MU was given 20 times in 15 min intervals to determine the trends in the activation level in a typical clinical mode. As well, a long-term (85 h over a long weekend) decay curve was measured to evaluate the long-term decay of room activation after a typical day of clinical linac use. A mathematical model for the activation level at the isocenter has been established and shown to be useful in explaining and predicting the induced activity levels for typical clinical and experimental conditions. The activation level for a 22 MeV electron beam was also measured and the result shows it is essentially negligible.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".