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Record W4241720246 · doi:10.17485/ijst/2009/v2i9.3

Replacing harmful refrigerant R22 in a bulk milk cooler.

2009· article· en· W4241720246 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndian Journal of Science and Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantGlobal-warming potentialEnvironmental scienceRetrofittingEnvironmentally friendlyProcess engineeringGreenhouse gasEngineeringHeat exchangerMechanical engineeringEcology

Abstract

fetched live from OpenAlex

Many milk coolers are presently using refrigerant R22 which has substantial ozone depleting potential along with high global warming potential. As per the commitment of Montreal and Kyoto protocol, R22 is required to be replaced by a suitable eco-friendly refrigerant and this paper explores the various options available. First the performance of 13 eco-friendly refrigerants was compared by simulating their performance with the help of CYCLE D. Then detailed study of binary and ternary mixture refrigerants has been done for selecting a Retrofit mixture for use in place of R22 in the existing milk cooler. Elucidating the performance,ODP and GWP values of refrigerants, it is clear that R1270 is best choice for replacing R22 with zero ODP and negligible GWP. Out of four mixtures, R32/R152 is best with zero ODP and low GWP. Keywords: Refrigerant, CFC22, Retrofitting, milk cooler

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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