Technical Note: Response measurement for select radiation detectors in magnetic fields
Bibliographic record
Abstract
PURPOSE: Dose response to applied magnetic fields for ion chambers and solid state detectors has been investigated previously for the anticipated use in linear accelerator-magnetic resonance devices. In this investigation, the authors present the measured response of selected radiation detectors when the magnetic field is applied in the same direction as the radiation beam, i.e., a longitudinal magnetic field, to verify previous simulation only data. METHODS: The dose response of a PR06C ion chamber, PTW60003 diamond detector, and IBA PFD diode detector is measured in a longitudinal magnetic field. The detectors are irradiated with buildup caps and their long axes either parallel or perpendicular to the incident photon beam. In each case, the magnetic field dose response is reported as the ratio of detector signals with to that without an applied longitudinal magnetic field. The magnetic field dose response for each unique orientation as a function of magnetic field strength was then compared to the previous simulation only studies. RESULTS: The measured dose response of each detector in longitudinal magnetic fields shows no discernable response up to near 0.21 T. This result was expected and matches the previously published simulation only results, showing no appreciable dose response with magnetic field. CONCLUSIONS: Low field longitudinal magnetic fields have been shown to have little or no effect on the dose response of the detectors investigated and further lend credibility to previous simulation only studies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".