Bibliographic record
Abstract
This paper aimed to investigate the refrigerant management regulations and research trend of alternative refrigerants for R-410A. More than 200 countries around the world agreed to limit the use of HFC(Hydro Fluoro Carbon) refrigerants through the 28th Montreal Protocol Conference in Kigali, Rwanda, in October 2016. The European Union has decided to ban the sale of HFC refrigerants and application systems of GWP(Global Warming Potential) 2500 or higher by applying the F-gas Regulation in 2020. AHRI(Air-conditioning, Heating and Refrigeration Institute) conducted the evaluation of alternative refrigerants. JRAIA(Japan Refrigeration and Air conditioning Industry Association) was studying various alternative refrigerants and paying attention to R-32 as a alternative refrigerant for R-410A. Recently, the HFO(Hydro fluoro olefin) refrigerant has been regarded as a promising alternative refrigerant due to low GWP and stable performance. But HFO non-azeotropic refrigerant mixtures are being developed and evaluated, because it is difficult to apply HFO refrigerant to residential air conditioner and heat pump because it shows low pressure characteristic at saturated temperature condition of general refrigeration system.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".