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Record W3120182237 · doi:10.1139/cjp-2020-0036

Atomic structure and radiative properties of He-like Ni<sup>26+</sup> ion in dense plasma

2021· article· en· W3120182237 on OpenAlexvenueno aff
Mayank Dimri, Dishu Dawra, A.K. Singh, Alok Jha, Rakesh Kumar Pandey, Man Mohan

Bibliographic record

VenueCanadian Journal of Physics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
FundersScience and Engineering Research BoardUniversity of Delhi
KeywordsPhysicsPrincipal quantum numberAtomic physicsIonPlasmaElectronRadiative transferRedshiftExcitationQuantumNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

The influence of plasma screening on the excitation energies and transition properties of He-like Ni26+ ion under strongly coupled plasma background has been analyzed. To perform the analysis, the multi-configuration Dirac–Fock method has been adopted by incorporating the ion sphere model potential as a modified interaction potential between the electron and the nucleus. For comparison purposes, parallel calculations have been carried out using the modified relativistic configuration interaction method. It is found that the transition energies corresponding to principal quantum number conserving transitions (Δn = 0) are blue shifted, whereas they are redshifted for the transitions where the principal quantum number is not conserved (Δn ≠ 0). The variation of transition probabilities and weighted oscillator strengths with free electron densities has also been studied. The present results should be advantageous in the modeling and diagnostics of astrophysical and laboratory plasmas.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.188
Teacher spread0.181 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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