Low-energy protons scanning of intentionally partially damaged silicon MESA radiation detectors
Bibliographic record
Abstract
The main aim of this work was to measure the spectroscopic response of intentionally damaged MESA silicon detectors. A uniformly damaged region was created using protons delivered by the Montreal University 6 MV tandem accelerator at different energies and fluences. Only the back half of the detector was damaged. The vacancy density created in the damaged region was built at a level of 7/spl times/10/sup 15/ vacancies/cm/sup 3/. The detector responses were scanned over their whole volume with protons of well defined ranges. Their response characteristics were studied using protons of 9 different energies. The highest energy was selected for allowing the protons to reach precisely the ohmic side (n/sup +/-side) of the 296 /spl mu/m thick detector. The scanning of the detector from the undamaged front side was performed with three different proton energies of ranges within the undamaged region. Two proton energies were selected for probing the transient region extending between the damaged and undamaged regions of the detector. Three energies of protons were chosen to probe the damaged region of the diode. The same set of energies was selected for the study of the detector spectroscopic features while illuminating the detector back side. The measured spectroscopic responses of the irradiated detectors were compared to the response of the undamaged detector. The charge collection efficiency (CCE) in the undamaged, transient and damaged regions of the detector volume was determined.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".