A systematic characterization of plastic scintillation dosimeters response in magnetic fields: I. Experimental measurements
Bibliographic record
Abstract
Abstract Objective. This study aims to evaluate the performance of five distinct plastic scintillation dosimeters (PSDs) in magnetic fields, as well as to validate the accuracy of the hyperspectral approach for stem-effect correction. The effect of the magnetic field on different base core materials and components within the PSDs was also investigated, as well as the effect of field size and orientation. Approach. Each PSD was placed at 5 cm depth in a water tank inside an electromagnet gap. Magnetic fields, between 0 and 1.5 T, were set to be perpendicular to the 6 MeV photon beam and to the PSD axis. The detector axis was either parallel or perpendicular to the photon beam. Different field sizes were used. The hyperspectral technique was validated and used to determine the scintillation, fluorescence and Cherenkov components at different magnetic fields. Main results. The hyperspectral method accurately removes stem effects in magnetic fields, even when calibration is performed at 0 T. The stem light yield shows good agreement with clear fiber measurements, with relative differences within 2.0%. In the parallel orientation, the corrected PSD response is highly symmetric relative to magnetic field polarity, with a maximum variation of only 0.2% from unity. Scintillation light yield increases with magnetic field by 3.6%–6.25% depending on PSD properties. Cherenkov light yield varies up to 230% and down to 0.30% of the 0 T value, depending on magnetic field polarity. The impact of magnetic fields depends primarily on the properties of the scintillator itself, with polyvinyltoluene-based probes showing greater sensitivity than polystyrene-based probes. The inclusion of a wavelength shifter has minimal on the magnetic field’s effect on scintillation light yield. Normalized scintillation light yield decreases with smaller field sizes. Significance. PSDs are well-suited for accurate dosimetry in magnetic fields, provided that accurate stem-effect correction techniques are applied. The scintillator properties play a significant role in determining the PSD’s sensitivity to magnetic fields. The hyperspectral method is a robust approach for accurate stem-effect removal in such conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".