Independent-electron analysis of the x-ray spectra from single-electron capture in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow><mml:mi>Ne</mml:mi></mml:mrow><mml:mrow><mml:mn>10</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math>collisions with He, Ne, and Ar atoms
Bibliographic record
Abstract
We present a theoretical study on the x-ray spectra from single-electron capture in 4.54 keV/amu ${\mathrm{Ne}}^{10+}$-He, -Ne, and -Ar collisions. Single-particle capture probabilities were calculated using the two-center basis generator method within the independent electron model. In this framework we investigated the effects of a time-dependent screening potential that models target response on capture cross sections and x-ray spectra. Excellent agreement is shown with the previously measured relative cross sections and x-ray spectra and calculations based on the classical trajectory Monte Carlo method using the no-response single-particle electron capture probabilities in a multinomial single-electron capture analysis. Our results demonstrate the importance of using this consistent statistical analysis of single-electron capture within the independent electron model; a requirement that a previous calculation for the same collision problem using the two-center atomic-orbital close-coupling method may not have considered.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".