THE TRANSITION OF CFCS AND HCFCS TO ALTERNATIVE REFRIGERANTS IN THE UNITED STATES
Bibliographic record
Abstract
The United States is one of the largest markets in the world for air-conditioning and refrigeration equipment, and was one of the first countries to sign the Montreal Protocol and complies with its obligations through a U.S. national law called the U.S. Clean Air Act of 1990. Phaseout of CFCs in the U.S. is well underway and manufacturers, in compliance with the law, will meet or exceed the requirements set forth in the Montreal Protocol. HCFC-22 is the most widely used refrigerant in the U.S. This is due to the proliferation of residential and small commercial unitary air-conditioning equipment which relies almost exclusively on HCFC-22. It is obvious that the phaseout of the production of HCFC-22, currently scheduled for the year 2020, will have a significant impact on the United States. The HCFC-22 Alternative Refrigerants Evaluation Program (AREP) was established by the Air-Conditioning and Refrigeration Institute (ART) to assist manufacturers in obtaining performance data on a multitude of HCFC-22 and R-502 alternatives. Several alternatives are found to perform almost as well, and sometimes better than the baseline refrigerant. No single alternative emerged as an universal replacement for all applications.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".