The probe‐format graphite calorimeter, Aerrow, for absolute dosimetry in ultrahigh pulse dose rate electron beams
Bibliographic record
Abstract
PURPOSE: The purpose of this investigation is to evaluate the use of a probe-format graphite calorimeter, Aerrow, as an absolute and relative dosimeter of high-energy pulse dose rate (UHPDR) electron beams for in-water reference and depth-dose-type measurements, respectively. METHODS: In this paper, the calorimeter system is used to investigate the potential influence of dose per pulses delivered up to 5.6 Gy, the number of pulses delivered per measurement, and its potential for relative measurement (depth-dose curve measurement). The calorimeter system is directly compared against an Advanced Markus ion chamber. The finite element method was used to calculate heat transfer corrections along the percentage depth dose of a 20-MeV electron beam. Monte Carlo-calculated dose conversion factors necessary to calculate absorbed dose-to-water at a point from the measured dose-to-graphite are also presented. RESULTS: The comparison of Aerrow against a fully calibrated Advanced Markus chamber, corrected for the saturation effect, has shown consistent results in terms of dose-to-water determination. The measured reference depth is within 0.5 mm from the expected value from Monte Carlo simulation. The relative standard uncertainty estimated for Aerrow was 1.06%, which is larger compared to alanine dosimetry (McEwen et al. https://doi.org/10.1088/0026-1394/52/2/272) but has the advantage of being a real-time detector. CONCLUSION: In this investigation, it was demonstrated that the Aerrow probe-type graphite calorimeter can be used for relative and absolute dosimetries in water in an UHPDR electron beam. To the author's knowledge, this is the first reported use of an absorbed dose calorimeter for an in-water percentage depth-dose curve measurement. The use of the Aerrow in quasi-adiabatic mode has greatly simplified the signal readout, compared to isothermal mode, as the resistance was directly measured with a high-stability digital multimeter.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".