Energy and integrated dose dependence of MOSFET dosimeter sensitivity for irradiation energies between and
Bibliographic record
Abstract
Since metal-oxide-semiconductor field effect transistors (MOSFETs) medical applications in radiotherapy and radiology are gaining popularity, evaluating them under radiation of different energies is of major interest. This study aims at a characterization of MOSFET sensitivity with regard to total integrated dose. Sensitivity is expressed by the water calibration factor (CFw) and allows the user to associate the voltage difference reading displayed by the device to a dose value in water at the MOSFET location. The CFw of seven p-type dual-bias MOSFETs were measured for several accumulated doses. The radiation sources used were a 60Co unit ((E)gamma: 1.25 MeV), an 192Ir high dose rate unit ((E)gamma: 380 keV), and an orthovoltage unit providing two x-ray energy spectra for tube voltages of 30 kV((E)gamma:14.8 KeV) and 150 kV((E)gamma:70.1 keV). The CFw value diminishes with increasing threshold voltage, especially for low-energy radiation. It was stable for 60Co irradiations, while it decreased 6%, 5%, and 15% for beam energies of 192Ir, 150 kV, and 30 kV, respectively. The decrease rate is higher for the first half of the device lifetime. This behavior is explained by an alteration of the effective electric field applied to the MOSFET during irradiation, caused by the accumulation of holes at the Si-SiO2 interface. It is strongly dependent on the nature of the radiation, and particularly affects low x-ray energies. A frequent calibration of the device for this radiation type is essential in order to achieve adequate measurement accuracy, especially in low-energy applications, such as superficial therapy, brachytherapy, and diagnostic and interventional radiology.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".