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Record W2913853808 · doi:10.3390/atoms7010015

Capture Cross Sections and Radiative Emission-Line Strengths for Slow Ne8+ Collisions with He and H2

2019· article· en· W2913853808 on OpenAlexafffund
Anthony C. K. Leung, Tom Kirchner

Bibliographic record

VenueAtoms · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsRadiative transferCollisionElectron captureElectronLine (geometry)Atomic physicsNuclear physicsGenerator (circuit theory)Computational physicsOpticsPower (physics)Computer science

Abstract

fetched live from OpenAlex

The Ne8+–He and –H2 collision systems are examined at impact speeds ranging between 0.17 and 0.4 a.u. Transition probabilities for electron capture are obtained using the two-center basis generator method performed within the independent-electron model. The aim of calculating capture cross sections for these collision systems is to provide new theoretical verification of previously reported experimental data and to provide aid for astrophysical X-ray studies. This study also examines the applicability of the independent-electron model with effective potentials to describe two-electron capture for these two systems. Comparisons of capture cross sections and radiative-emission counts with the available experimental and theoretical data show an overall good agreement.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.252
Teacher spread0.248 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

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