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Record W3087779494

study the effect of ecofriendly refrigerant in air conditioning

2020· article· en· W3087779494 on OpenAlexaboutno aff
Sachin Singh, Ravindra Randa

Bibliographic record

VenueJournal of Emerging Technologies and Innovative Research · 2020
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantGas compressorEvaporatorAir conditioningRefrigerationEnvironmentally friendlyEnvironmental scienceCoefficient of performanceChlorofluorocarbonProcess engineeringPower consumptionOzone layerMontreal ProtocolWaste managementThermodynamicsPower (physics)EngineeringOzoneMechanical engineeringMeteorologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

The use of chlorofluorocarbon and hydrochlorofluorocarbon is the major reason for ozone layer depletion and a greenhouse effect. The uses of a proposed choice of refrigerants have the following benefit such as (i) easily available in local places, (ii) less expensive, and (iii) an eco- friendly nature. The parameters to be investigated are the capacity of an evaporator, compressor power, coefficient of performance (COP) and, the cooling rate. Hence, this paper has given predilection to remove the adverse effects through the use of suitable eco-friendly refrigerant in air conditioning systems and, with the help of this EPR of refrigeration systems is also improved. This paper tells us about that refrigerant which is eco-friendly and having a better performance parameter.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.051
GPT teacher head0.357
Teacher spread0.306 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueJournal of Emerging Technologies and Innovative ResearchSame topicRefrigeration and Air Conditioning TechnologiesFrench-language works237,207