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Record W2054601927 · doi:10.1515/jnetdy.2010.004

Dynamic thermodiffusion theory for ternary liquid mixtures

2010· article· en· W2054601927 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Non-Equilibrium Thermodynamics · 2010
Typearticle
Languageen
FieldEngineering
TopicField-Flow Fractionation Techniques
Canadian institutionsToronto Metropolitan University
FundersCanadian Space AgencyEuropean Space Agency
KeywordsTernary operationThermodynamicsDiffusionBasis (linear algebra)Flow (mathematics)Thermal diffusivityThermalStatistical physicsExpression (computer science)MechanicsMaterials scienceComputer scienceMathematicsPhysicsGeometry

Abstract

fetched live from OpenAlex

Following the non-equilibrium thermodynamics approach, we develop expressions for the calculation of the thermal diffusion coefficients in a ternary system. On the basis of some physical justifications, we approximate the net heat of transport with the activation energy of viscous flow. In parallel, we revisit the Kempers model and propose new expressions for the estimation of the thermal diffusion factors in a ternary mixture. The proposed expressions are based on a dynamic modeling approach, as they incorporate the activation energy of viscous flow, which is a fluid flow property and contains the effects of some of the parameters that govern thermodiffusion. The proposed expressions, the Kempers and Ghorayeb–Firoozabadi–Shukla models are evaluated against the experimental data. Our expression which was developed on the basis of the Kempers approach has the best performance.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.939
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.004
GPT teacher head0.236
Teacher spread0.232 · 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