First determination of ground state electromagnetic moments of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi>Fe</mml:mi><mml:mprescripts/><mml:none/><mml:mn>53</mml:mn></mml:mmultiscripts></mml:math>
Bibliographic record
Abstract
The hyperfine coupling constants of neutron deficient $^{53}\mathrm{Fe}$ were deduced from the atomic hyperfine spectrum of the $3{d}^{6}4{s}^{2}{\phantom{\rule{4pt}{0ex}}}^{5}{D}_{4}\phantom{\rule{4pt}{0ex}}\ensuremath{\leftrightarrow}\phantom{\rule{4pt}{0ex}}3{d}^{6}4s4p{\phantom{\rule{4pt}{0ex}}}^{5}{F}_{5}$ transition, measured using the bunched-beam collinear laser spectroscopy technique. The low-energy $^{53}\mathrm{Fe}$ beam was produced by projectile-fragmentation reactions followed by gas stopping, and used for the first time for laser spectroscopy. Ground state magnetic-dipole and electric-quadrupole moments were determined as $\ensuremath{\mu}=\ensuremath{-}0.65(1)\phantom{\rule{0.16em}{0ex}}{\ensuremath{\mu}}_{N}$ and $Q=+35(15)\phantom{\rule{0.28em}{0ex}}{e}^{2}{\mathrm{fm}}^{2}$, respectively. The multiconfiguration Dirac-Fock method was used to calculate the electric field gradient to deduce $Q$ from the quadrupole hyperfine coupling constant, since the quadrupole coupling constant has not been determined for any Fe isotopes. Both experimental values agree well with nuclear shell model calculations using the GXPF1A effective interaction performed in a full $fp$ shell model space, which support the soft nature of the $^{56}\mathrm{Ni}$ nucleus.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".