MétaCan
Menu
Back to cohort
Record W4384648185 · doi:10.17816/rf321629

ENERGY EFFICIENCY ANALYSIS METHODS OF REFRIGERATION PLANTS

2023· article· en· W4384648185 on OpenAlexaboutno aff
Maksim S. Talyzin

Bibliographic record

VenueRefrigeration Technology · 2023
Typearticle
Languageen
FieldComputer Science
TopicEngineering Education and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsEnergy consumptionLegislationBusinessEfficient energy useElectricityConsumption (sociology)Russian federationEnvironmental economicsAir conditioningEnergy policyNatural resource economicsEnvironmental protectionEnvironmental scienceEconomic policyEngineeringEconomicsPolitical scienceRenewable energyLawMechanical engineering

Abstract

fetched live from OpenAlex

Cold supply systems occupy a leading place in many industries. Their improvement is currently associated with two main areas: energy saving and ecology. The problems of energy saving are paid great attention both at the state level (Federal Law No. 261-FZ "On Energy Saving and on Improving Energy Efficiency and on Amending Certain Legislative Acts of the Russian Federation") and by the owners of refrigeration equipment. The costs of electricity consumed by cold supply systems make up a significant part both in the total balance of energy consumption of the enterprise (for catering enterprises it ranges from 48% to 60%) and in the country's total energy consumption (for example, the share of energy consumption of air conditioning systems in Europe ranges from 2% to 6%). Along with this, the ratification by the Russian Federation of Montreal (Resolution No. 539 of the Government of the Russian Federation of 27.08.2005) and the Kyoto (FZ 128-FZ of November 4, 2004) Protocols, the entry into force of European Regulations 517/2014 governing the decommissioning of refrigerants with global warming potential GWP above 2500, for example, the R404A and R507A currently in active use, as well as the adoption by the Russian Federation of new environmental legislation in connection with the signing of the Paris Agreement, leads to the need to use new refrigerants, which are not always more efficient than traditionally used solutions and require changes to the technological scheme of refrigeration systems. These factors lead to the need to improve efficiency calculation methods based on classical methods of thermodynamic analysis.

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)0.001
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.013
GPT teacher head0.314
Teacher spread0.301 · 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
GenreMethods

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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRefrigeration TechnologySame topicEngineering Education and TechnologyFrench-language works237,207