Role of projectile electrons for target-recoil-charge-state production in intermediate-energy B<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mrow/><mml:mrow><mml:mn>2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math>-Ne collisions
Bibliographic record
Abstract
We apply an independent electron model to study $q$-fold target-charge-state production in 25--600 keV/nucleon B${}^{2+}$-Ne collisions for which experimental and theoretical results were published recently [W. Wolff et al., Phys. Rev. A 84, 042704 (2011)]. The model treats projectile and target electrons using a common potential and makes use of a single-determinant wave function for the combined system. The calculated total cross sections for positive recoil ion production as well as for Ne${}^{q+}$ production ($q=1,...,4$) determined in coincidence with an unchanged projectile charge state agree well with experiment where available, i.e., in the 30--400 keV/nucleon energy range. At energies below 200 keV/nucleon the projectile electrons are shown to play a crucial role in reproducing the experimental data for $q=1,...,4$. For the $q\ensuremath{\ge}2$ channels the inclusion of projectile electron contributions is needed even at energies above 200 keV/nucleon in order to reproduce the experimental data. As expected, the predictions for the $q=5$ recoil charge state overestimate the experimental data due to a failure of the independent electron model for this extreme channel.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".