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Record W2984066560 · doi:10.1088/1402-4896/ab56ad

Investigation of the doubly excited <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow/> <mml:mrow> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> <mml:msup> <mml:mrow> <mml:mi>P</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>o</mml:mi> </mml:mrow> </mml:msup> </mml:math> resonance series of the O <sup>6+</sup> ion under the <i>N</i>  = 3 threshold of O <sup>7+</sup>

2019· article· en· W2984066560 on OpenAlexafffund
Samira Barmaki, Marc-André Albert, Stéphane Laulan

Bibliographic record

VenuePhysica Scripta · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExcited stateResonance (particle physics)Series (stratigraphy)IonPhysicsAtomic physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract We theoretically investigate the doubly excited 1 P o resonance series of the O 6+ ion converging towards the N = 3 threshold. No experimental measurements of the energy positions E and the widths Γ for the states belonging to the different series have been reported so far. On the theoretical side, the existing results are rare and not in a perfect agreement. We report in this work accurate results of the resonant parameters ( E , Γ) for the 1 P o resonance states of the ion obtained by using a B -spline based spectral approach combined with the complex rotation method. Our method has the numerical advantage to generate the resonant parameters in a single calculation. It also allows the identification of the states that share similar angular correlation pattern, which helps in their classification into distinct series. Results of the resonant parameters for the high-lying 1 P o states are being reported for the first time.

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)0.001
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 score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.017
GPT teacher head0.221
Teacher spread0.205 · 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
Published2019
Admission routes2
Has abstractyes

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