Fine Structure Analysis of the Configuration System of V II. Part I: Even-Parity Levels
Bibliographic record
Abstract
Using a linked-parameter technique of level-fitting calculations in a multi configuration basis, a parametric analysis of fine structure (fs) for even-parity levels of V II, involving six configurations, has been performed. This led us to exchange the assignments of two triplets, 3d3(2F)4s c 3F and 3d4 d 3F, reported in earlier analyses as being located at 30,300 cm-1 and 30,600 cm-1, respectively. This is confirmed by experimental hyperfine structure (hfs) A constants, used as fingerprints. Moreover, the current singlet 3d24s2 1D2 position is likely too high. The fs parameters, magnetic Landé g-factors, and the percentage of leading eigenvectors of levels are calculated. We present also predicted singlet, triplet and quintet positions for missing experimental levels up to 100,000 cm-1. The single-electron hfs parameters are determined in their entirety for 51V II for the model space (3d + 4s)4 with good accuracy. For the model space (3d + 4s)4 of 51V II the single-electron hfs parameters are computed; furthermore, our achieved theoretical evaluations of the single-electron hfs parameters, thanks to the use of ab initio calculations, reinforce the validity of these hfs parameter values, deduced from experimental data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".