Implantation profile of Na22 continuous energy spectrum positrons in silicon
Bibliographic record
Abstract
The implantation profile of positrons emitted from a continuous energy spectrum source of Na22 in close proximity to a silicon target is modeled. The primary motivation is the use of positron lifetime spectroscopy to characterize layers of defects such as those created by ion irradiation, usually deemed accessible only to techniques which utilize slow positrons. The model combines the Makhov profile, used with considerable success to describe the profile of low energy (<30keV) monoenergetic positrons, with the well-established, universal β-decay energy spectrum. The success of this approach is verified by measuring the fractions of positrons absorbed in thinned silicon samples. This verification utilizes lifetime measurements performed on silicon in a bilayer sandwich configuration with copper as a backing. The model accounts for the uncertainty in the positron backscattering at the silicon∕copper interface. An optimal fit of the model to the experimental data requires that the parameter defining the mean depth of the Makhov profile (usually denoted r) is energy dependent. An example of application is provided in the form of a positron lifetime measurement of defects in silicon introduced by 1.5MeV proton irradiation. Excellent agreement is found between the lifetime data and those obtained using a slow positron technique.
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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 | 0.001 | 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".