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Record W2045718837 · doi:10.1103/physrevlett.96.255005

Energy Loss of a Charged Particle Moving over a 2D Strongly Coupled Dusty Plasma

2006· article· en· W2045718837 on OpenAlexaff
Lu-Jing Hou, Z. L. Mišković, Ke Jiang, You‐Nian Wang

Bibliographic record

VenuePhysical Review Letters · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsProjectileDusty plasmaPhysicsPlasmaAtomic physicsCharge (physics)Charged particleCoupling (piping)Nonlinear systemParticle (ecology)Random phase approximationMolecular dynamicsPhase (matter)IonQuantum mechanicsMaterials science

Abstract

fetched live from OpenAlex

We use molecular dynamics (MD) simulation to evaluate the energy loss of a charged projectile moving parallel to a two-dimensional strongly coupled dusty plasma and compare the results with those obtained from the quasilocalized charge approximation (QLCA) and the Vlasov-random phase approximation. Good agreement is found between the QLCA and MD results when the projectile-dust coupling is weak. In the opposite regime, nonlinear effects in the dust-layer response render the QLCA model increasingly inadequate for calculating the energy losses at low projectile speeds.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.237
Teacher spread0.227 · 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

Citations20
Published2006
Admission routes1
Has abstractyes

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