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Record W2788678574 · doi:10.11575/prism/30255

Positional and Orientational Configurational Temperatures from Computer Simulation

2001· article· en· W2788678574 on OpenAlexfundno aff
Peter G. Kusalik, Ariel A. Chialvo, J.M. Simonson, Peter T. Cummings

Bibliographic record

VenuePRISM (University of Calgary) · 2001
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsnot available
FundersOak Ridge National LaboratoryNatural Sciences and Engineering Research Council of CanadaBasic Energy SciencesUT-BattelleBattelleU.S. Department of Energy
KeywordsComputer scienceChemistryStatistical physicsPhysics

Abstract

fetched live from OpenAlex

We define two configurational temperatures associated with the positional r N and orientational co N portions of the configurational phase space of the molecules in a system according to Hirschfelder's hypervirial theorem, and implement their calculation by Monte Carlo and molecular dynamics simulations.We use a simple quadrupolar Lennard-Jones fluid at normal conditions and the TIP4P model at low temperature to illustrate the use of these quantities to test the correctness of Monte Carlo simulation protocols, and as a new tool in the study of the poorly understood behavior of supercooled water.

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)0.003
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.005
GPT teacher head0.181
Teacher spread0.176 · 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

Citations0
Published2001
Admission routes1
Has abstractno

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