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Record W2018878270 · doi:10.1103/physreve.63.016401

Nonhydrodynamic aspects of electron transport near a boundary: The Milne problem

2000· article· en· W2018878270 on OpenAlexaff
A. V. Vasenkov, Bernie D. Shizgal

Bibliographic record

VenuePhysical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · 2000
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsPhysicsElectronBoundary (topology)Momentum (technical analysis)Boundary value problemDistribution functionBoltzmann equationPosition and momentum spaceLegendre polynomialsFokker–Planck equationSpace (punctuation)Atomic physicsQuantum electrodynamicsQuantum mechanicsDifferential equationMathematical analysis

Abstract

fetched live from OpenAlex

The nonhydrodynamic behavior of electrons near a boundary is studied with the Milne problem of transport theory. A system of electrons dilutely dispersed in a heat bath of atomic moderators is considered in the positive one-dimensional spatial half-space with an absorbing boundary at the origin which mimics an electrode. A flux of electrons is assumed to originate at an infinite distance from the boundary. The Fokker-Planck equation for the electron distribution function in space and velocity is considered. The density and temperature profiles are determined, and the departure from hydrodynamic behavior near the boundary is studied. Argon and helium are chosen as the moderators, and results with different cross sections are obtained. The Fokker-Planck equation is solved with an expansion in Legendre and Speed polynomials, and compared wherever possible with results obtained with a Monte Carlo simulation. The behavior near the boundary is shown to be strongly influenced by the Ramsauer-Townsend minimum in the electron-Ar momentum transfer cross section.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.301
Teacher spread0.293 · 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 teacher head, not a consensus.

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

Citations5
Published2000
Admission routes1
Has abstractyes

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