Hyperfine quenching of the metastable 4s4p <sup>3</sup>P<sub>0</sub> and <sup>3</sup>P<sub>2</sub> states of Zn-like ions<sup>1</sup>This article is part of a Special Issue on the 10th International Colloquium on Atomic Spectra and Oscillator Strengths for Astrophysical and Laboratory Plasmas.
Bibliographic record
Abstract
The hyperfine-induced 4s4p 3P0,2–4s2 1S0 transition rates for Zn-like ions with Z = 30–66 are calculated using a large scale relativistic configuration-interaction method. Comparisons are made between different approaches to hyperfine quenching studies, and discussions are given to the significance of various contributions. For the 3P0 state, the effect of the 1P1 state on hyperfine quenching is found to be quite substantial and cannot be ignored in spite of the large energy separation. For the 3P2 state, hyperfine quenching leads to different decay rates to the ground state for different hyperfine levels and the induced decays can dominated over the unperturbed M2 transition. The present results are compared with the other theoretical predictions, and reasons for the discrepancies are discussed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".