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Record W2029187433 · doi:10.1002/cjce.5450790309

An accurate model for prediction of gas hydrate formation conditions in mixtures of aqueous electrolyte solutions and alcohol

2001· article· en· W2029187433 on OpenAlexvenueno aff
Jafar Javanmardi, Mahmood Moshfeghian, R.N. Maddox

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsElectrolyteHydrateClathrate hydrateAqueous solutionThermodynamicsAlcoholChemistryActivity coefficientPhysical chemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract A new thermodynamic model for calculating the hydrate formation temperature of different hydrate formers in aqueous solutions of both electrolytes and a single alcohol has been presented. This method uses a generalization of the Aasberg‐Petersen model for water activity. For calculation of water activity in the presence of electrolytes, the effect of alcohols was taken into account without using any new fitting parameters. The results are in good agreement with published experimental data. Calculated values of the hydrate formation temperature in the presence of alcohols and electrolytes are compared with those obtained by other existing models. The average absolute error of hydrate formation temperature for 524 available experimental data points is about 0.87 K.

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 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: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.209
Teacher spread0.195 · 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 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

Citations64
Published2001
Admission routes1
Has abstractyes

Explore more

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