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Record W658713439

Rarefied gas dynamics : 23rd International Symposium, Whistler, British Columbia, Canada, 20-25 July 2002

2003· book· en· W658713439 on OpenAlexaboutno aff
Andrew Ketsdever, E. P. Muntz

Bibliographic record

VenueAmerican Institute of Physics eBooks · 2003
Typebook
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsnot available
Fundersnot available
KeywordsSpace physicsAerospace engineeringMicroscale chemistryDirect simulation Monte CarloPhysicsHypersonic speedMonte Carlo methodComputational physicsMechanicsEngineeringGeophysics
DOInot available

Abstract

fetched live from OpenAlex

The papers in these proceedings were peer reviewed. The RGD Symposia are highly inter-disciplinary and encompass all aspects of rarefaction and non-equilibrium phenomena in gases. Rarefied flow phenomena include the mechanics and physics of low density gases and the analysis of flows which take place on a spatial scale comparable to the mean free path of a gas. Topics covered include: Kinetic theory and transport theory; numerical methods including direct simulation Monte Carlo and molecular dynamics; gas-surface phenomena; nano- and microscale flows; molecular beams, atom and molecular optics; clusters and aerosols; external flows including space and vacuum technologies; plume flows; hypersonic flows; molecular collision dynamics; relaxation processes; ionized gas flows; physics of the space environment; plasma processing; experimental techniques; diagnostics including laser induced fluorescence and electron beams; applications. With the increase in space activities and microfabrication capabilities, new themes have emerged including rarefied hypersonic flows, non-equilibrium gases, plasma processing, nano- and micro-scale flows at relatively high pressures, along with parallel and hybrid computational developments. Because the RGD Symposia are recognized as the principle forum for the presentation of recent advances in this field, it is a must for engineers and scientists in a variety of specialties.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.499
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2003
Admission routes1
Has abstractyes

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