The Auger effect in physical and biological research
Bibliographic record
Abstract
PURPOSE: The paper reports on progress in physics of radiationless transitions and new Auger spectra of (125)I and (124)I. We report progress in Monte Carlo track structure simulation of low energy electrons comprising majority electrons released in decay most Auger emitters. MATERIALS AND METHODS: The input data for electron capture (EC) and internal conversion(IC) were obtained from various physics data libraries. Monte Carlo technique was used for the simulation of Auger electron spectra. Similarly, electron tracks were generated using Monte Carlo track structure methods. RESULTS: Data are presented for the EC, IC and binding energy (BE) of radionuclides (124)I and (125)I. For each of the radionuclides (125)I and (124)I some examples of electron spectra of individual decays are given. Because most Auger electrons are low energy and short range, data and a short discussion are presented on recent Monte Carlo track structure development in condensed media and their accuracy. CONCLUSIONS: Accuracy of electron spectra calculated in the decay of electron shower by Auger emitting radionuclides depends on availability of accurate physics data. There are many gaps in these libraries and there is a need for detailed comparison between analytical method and Monte Carlo calculations to refine the method of calculations. On simulation of electron tracks, although improved models for sub-keV electron interaction cross sections for liquid water are now available, more experimental data are needed for benchmarking. In addition, it is desirable to make data and programs for calculations of Auger spectra available online for use by students and researchers.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".