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Record W1968027089 · doi:10.1631/jzus.2007.a0724

Needs of thermodynamic properties measurements and modeling in the frame of new regulations on refrigerants

2007· article· en· W1968027089 on OpenAlexaboutno aff
Christophe Coquelet, Dominique Richon

Bibliographic record

VenueJournal of Zhejiang University. Science A · 2007
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantArtificial neural networkMontreal ProtocolFrame (networking)Computer scienceEnvironmental scienceGlobal-warming potentialProcess engineeringBiochemical engineeringGreenhouse gasThermodynamicsMachine learningChemistryEngineeringOzone layerHeat exchangerEcology

Abstract

fetched live from OpenAlex

In 1987, the Montreal Protocol prohibited the worldwide use and production of chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) and hydro fluorocarbons (HFCs) were proposed as alternative refrigerants. Unfortunately, HFCs have non negligible global warning potential and therefore new refrigerants must be proposed or old refrigerants must be used associated with HFC. Accurate experimental thermodynamic data and predictive techniques are required for better understanding of the performance of the newly proposed refrigerants. In this communication, experimental techniques based on either analytic or synthetic methods are first described. Data are reported. Then two newly developed predictive models based on thermodynamic approach with the isofugacity criterion and artificial neural network method are presented. The results can provide better evaluation of refrigerants, especially with the aim of studying global warning effects.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.236
Teacher spread0.179 · 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 designTheoretical or conceptual
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

Citations3
Published2007
Admission routes1
Has abstractyes

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Same venueJournal of Zhejiang University. Science ASame topicPhase Equilibria and ThermodynamicsFrench-language works237,207