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Record W4402028392 · doi:10.48550/arxiv.2408.06940

Spherical-oblate shape coexistence in $^{94}$Zr from a model-independent analysis

2024· preprint· en· W4402028392 on OpenAlexaff
N. Marchini, M. Rocchini, M. Zielińska, A. Nannini, D. T. Doherty, N. Gavrielov, Patricia E. Garrett, K. Hadyńska-Klęk, A. Goasduff, D. Testov, S. Bakes, D Bazzacco, G. Benzoni, Tom Berry, D. Brugnara, F. Camera, W. N. Catford, M. Chiari, F. Galtarossa, N. Gelli, A. Gottardo, A. Gozzelino, A. Illana, J. M. Keatings, D. Mengoni, L. Morrison, D. R. Napoli, M. Ottanelli, P. Ottanelli, G. Pasqualato, F Recchia, S. Riccetto, M. Scheck, M. Siciliano, J.J. Valiente Dobón, I. Zanon

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOblate spheroidPhysicsGeometryStatistical physicsClassical mechanicsTheoretical physicsMathematics

Abstract

fetched live from OpenAlex

Low-lying states of 94 Zr were investigated via low-energy multi-step Coulomb excitation. From the measured γ -ray yields, 16 reduced E2 transition probabilities between low-spin states were determined, together with the spectroscopic quadrupole moments of the 2 1 , 2 + states. Based on this information, for the first time in the Zr isotopic chain, the shapes of the 0 1 , 2 + states including their deformation softness were inferred in a model-independent way using the quadrupole sum rules approach. The ground state of 94 Zr possesses a rather diffuse shape associated with a spherical configuration, while the 0 2 + state is triaxial tending towards oblate and more strongly deformed. The observed features of shape coexistence in 94 Zr are consistent with both Monte-Carlo shell-model predictions and IBM-CM calculations, and provide model-independent constraints on the shape character assigned in the IBM-CM to the intruder configuration in 92–96 Zr.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.168
Teacher spread0.125 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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