A Monte Carlo Based Development of a Cavity Theory for Solid State Detectors Irradiated in Electron Beams
Bibliographic record
Abstract
Recent Monte Carlo simulations have shown that the assumption in the small cavity theory (and the extension of the small cavity theory by Spencer-Attix) that the cavity does not perturb the electron fluence is seriously flawed. For depths beyond dmax not only is there a significant difference between the energy spectra in the medium and in the solid cavity material but there is also a significant difference in the number of low-energy electrons which cannot travel across the solid cavity and hence deposit their dose in it (i.e. stopper electrons whose residual range is less than the cavity thickness). The number of these low-energy electrons that are not able to travel across the solid state cavity increases with depth and effective thickness of the detector. This also invalidates the assumption in the small cavity theory that most of the dose deposited in a small cavity is delivered by crossers. Based on Monte Carlo simulations, a new cavity theory for solid state detectors irradiated in electron beams has been proposed as: Dmed(p) = meanDdet(p) x s(med,det)S-A x gamma(p)c x S(T) where Dmed(p) is the dose to the medium at point p. MeanDdet(p) is the average detector dose to the same point, s(med,det)S-A is the Spencer-Attix mass collision stopping power ratio of the medium to the detector material, gamma(P)c is the electron fluence perturbation correction factor and S(T) is a stopper-to-crosser correction factor to correct for the dependence of the stopper-to-crosser ratio on depth and the effective cavity size. Monte Carlo simulations have been computed for all the terms in this equation. The new cavity theory has been tested against the Spencer-Attix cavity equation as the small cavity limiting case and also Monte Carlo simulations.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".