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Record W2104251266 · doi:10.5194/angeo-29-123-2011

Nonlinear electrostatic ion-acoustic "oscilliton" waves driven by charge non-neutrality effects

2011· article· en· W2104251266 on OpenAlexafffund
Zhenguo Ma, Akira Hirose, W. Liu

Bibliographic record

VenueAnnales Geophysicae · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsUniversity of SaskatchewanCanadian Space Agency
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsAmplitudeSawtooth waveAtomic physicsEnvelope (radar)Nonlinear systemExcited stateIonComputational physicsQuantum electrodynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract. Nonlinear "oscilliton" structures features a low-frequency (LF) solitary envelope, the amplitude of which is modulated violently by superimposed high-frequency (HF) oscillations. We have studied the charge non-neutrality effects on the excitation of electrostatic ion-acoustic (IA) oscillitons. A two-fluid, warm plasma model is employed, and a set of nonlinear self-similar equations is solved in a cylindrical geometry. Under charge-neutrality conditions, three conventional IA structures (namely, sinusoidal, sawtooth, and spicky/bipolar) are obtained. By contrast, under charge non-neutrality conditions, oscilliton structures are excited, where the LF envelope is in the sound-wave (SW) mode, while the HF ingredients include the IA mode and the ion-Langmiur (IL) mode. The amplitudes of the SW wave are violently modulated by the IA oscillations, whereas the upward sides of the IA amplitudes are modulated by the IL oscillations of smaller amplitudes, and the downward sides are modulated by hybrid IA/IL oscillations. The nonlinear oscillitons are found to be dependent not only upon the input parameters (e.g., the Mach number, the Debye length, and the initial temperature of particles), but on initial conditions as well.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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 designTheoretical or conceptual
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

Citations6
Published2011
Admission routes2
Has abstractyes

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