High-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>K</mml:mi></mml:math>, two-quasiparticle states in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi>Gd</mml:mi><mml:mprescripts/><mml:none/><mml:mn>160</mml:mn></mml:mmultiscripts></mml:math>
Bibliographic record
Abstract
Excited states in $^{160}\mathrm{Gd}$ were populated via $\ensuremath{\beta}$ decay from the low- and high-spin isomers in $^{160}\mathrm{Eu}$. The high-spin, ${K}^{\ensuremath{\pi}}={5}^{\ensuremath{-}}$ state feeds several two-quasiparticle levels, as well as a sequence associated with a $\ensuremath{\gamma}$ vibration and a ${K}^{\ensuremath{\pi}}={4}^{+}$, hexadecapole vibrational structure. The decay scheme was significantly improved with the observation of new transitions and states when compared with the two competing level schemes from over four decades ago. Configuration assignments for some of the multiquasiparticle levels have been suggested, based upon decay properties, systematics from neighboring nuclei, and comparisons with theoretical calculations. In addition, 15 new low-spin states and approximately 60 new transitions were observed resulting from the decay of the low-spin $^{160}\mathrm{Eu}$ isomer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.008 |
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".