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Record W3137757506 · doi:10.1139/cjp-2020-0296

Exploring the α-decay chain of <sup>302</sup>122 within relativistic mean-field formalism

2020· article· en· W3137757506 on OpenAlexvenueno aff
M. Panigrahi, R. N. Panda, M. Bhuyan, S. K. Patra

Bibliographic record

VenueCanadian Journal of Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsExcited stateFormalism (music)PairingAtomic physicsBinding energyIsotopeAxial symmetryDecay chainNeutronGround stateNeutron numberMean field theoryRADIUSRange (aeronautics)Nuclear physicsQuantum mechanicsNeutron temperature

Abstract

fetched live from OpenAlex

The ground and first excited state structural properties, like binding energy, charge radius, deformation parameter, pairing energy, and two-neutron separation energy, for the isotopic chain of Z = 122 are analysed. The axially deformed relativistic mean-field formalism with NL3* force parameter is used for the present analysis. Based on the analysis of binding energy per particle, chemical potential, and single-particle spacing, we predict the isotopes of Z = 122 with N = 180, 182, and 184 are the possible stable nuclei over the considered isotopic chain. The α-decay energies and the decay half-lives of 302122 chains are investigated using four different empirical formulae. The results of our calculations are compared with the available experimental data and finite range droplet model predictions. We also established a correlation for the decay energy with the half-lives for the considered α-decay chains for various empirical formulae.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.256
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2020
Admission routes1
Has abstractyes

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