Cross-shell excited configurations in the structure of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi>Si</mml:mi><mml:mprescripts/><mml:none/><mml:mn>34</mml:mn></mml:mmultiscripts></mml:math>
Bibliographic record
Abstract
The cross-shell excited states of $^{34}\mathrm{Si}$ have been investigated via $\ensuremath{\beta}$ decays of the ${4}^{\ensuremath{-}}$ ground state and the ${1}^{+}$ isomeric state of $^{34}\mathrm{Al}$. Since the valence protons and valence neutrons occupy different major shells in the ground state as well as the intruder ${1}^{+}$ isomeric state of $^{34}\mathrm{Al}$, intruder levels of $^{34}\mathrm{Si}$ are populated via allowed $\ensuremath{\beta}$ decays. Spin assignments to such intruder levels of $^{34}\mathrm{Si}$ were established through $\ensuremath{\gamma}\text{\ensuremath{-}}\ensuremath{\gamma}$ angular correlation analysis for the negative-parity states with dominant configurations ${(\ensuremath{\nu}{d}_{3/2})}^{\ensuremath{-}1}\ensuremath{\bigotimes}{(\ensuremath{\nu}{f}_{7/2})}^{1}$ as well as the positive-parity states with dominant configurations ${(\ensuremath{\nu}sd)}^{\ensuremath{-}2}\ensuremath{\bigotimes}{(\ensuremath{\nu}{f}_{7/2}{p}_{3/2})}^{2}$. The configurations of such intruder states play crucial roles in our understanding of the $N=20$ shell gap evolution. A configuration interaction model derived from the FSU Hamiltonian was utilized in order to interpret the intruder states in $^{34}\mathrm{Si}$. Shell model interaction derived from a more fundamental theory with the valence space in medium similarity renormalization group method was also employed to interpret the structure of $^{34}\mathrm{Si}$.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".