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Record W2290589759 · doi:10.2172/1228765

Energy Efficient Commercial Refrigeration with Carbon Dioxide Refrigerant and Scroll Expanders

2013· report· en· W2290589759 on OpenAlexaboutno aff
John Dieckmann

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantRefrigerationEnvironmental scienceGlobal-warming potentialCarbon dioxideMontreal ProtocolOzoneVapor-compression refrigerationEnergy consumptionWaste managementGreenhouse gasProcess engineeringOzone layerChemistryEngineeringHeat exchangerMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Current supermarket refrigeration systems are built around conventional fluorocarbon refrigerants – HFC-134a and the HFC blends R-507 and R404A, which replaced the CFC refrigerants, R-12 and R-502, respectively, used prior to the Montreal Protocol phase out of ozone depleting substances. While the HFC refrigerants are non-ozone depleting, they are strong greenhouse gases, so there has been continued interest in replacing them, particularly in applications with above average refrigerant leakage. Large supermarket refrigeration systems have proven to be particularly difficult to maintain in a leak-tight condition. Refrigerant charge losses of 15% of total charge per year are the norm, making the global warming impact of refrigerant emissions comparable to that associated with the energy consumption of these systems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.217
Teacher spread0.203 · 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.

Study designNot applicable
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

Citations1
Published2013
Admission routes1
Has abstractyes

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