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Record W1983903038 · doi:10.1021/ie051204x

Prediction of Gas Hydrate Formation Conditions in the Presence of Methanol, Glycerol, Ethylene Glycol, and Triethylene Glycol with the Statistical Associating Fluid Theory Equation of State

2006· article· en· W1983903038 on OpenAlexaff
Xiao‐Sen Li, Hui‐Jie Wu, Peter Englezos

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of British Columbia
FundersChinese Academy of Sciences
KeywordsTriethylene glycolEthylene glycolEquation of stateClathrate hydrateMethanolChemistryThermodynamicsHydrateGlycerolEthyleneOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

The statistical associating fluid theory (SAFT) equation of state is employed for the prediction of the thermodynamic inhibiting effect of methanol, glycerol, ethylene glycol, and triethylene glycol on gas hydrate formation. The results were found to be in satisfactory to excellent agreement with experimental data. The SAFT equation takes into account hard-sphere repulsion, hard chain formation, dispersion, and association. This enables this model to be able to correlate and predict successfully systems containing water, alcohols, and hydrocarbons for which traditional cubic equations of state fail in general.

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)0.004
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.041
GPT teacher head0.268
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 teacher head, 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

Citations91
Published2006
Admission routes1
Has abstractyes

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