Bibliographic record
Abstract
Hydrofluorocarbons (HFCs) are a group of organic compounds that contain carbon, fluorine, and hydrogen. They are by-products of industrial manufacturing and were introduced as a replacement for chlorofluorocarbons and other ozone depleting substances. However, though HFCs have zero ozone depletion potential (ODP), they have intrinsic and significant global warming potential (GWP), typically in the range of 1,000 to 3,000 times that of CO2. Thus, they are among the six key greenhouse gases listed in the Kyoto Protocol for emission reduction. Other greenhouse gases listed by the protocol are CO2, CH4, N2O, PFCs, SF6, and HFCs. Industry and government are collaborating on research and development, communication, and other activities to find new technologies, designs, and processes to manage these emissions. The emissions management is occurring through non-regulatory means, voluntary measures, and industry-government collaborations. The air-conditioning and commercial refrigeration industry has particularly contributed to the success of the management process. HFCs are generally colourless and odourless gases at environmental temperatures and are mostly chemically unreactive. They are non-flammable, having very low toxicity; they are recyclable, and highly energy efficient. There has been a significant growth in the market for HFCs because they have been identified as important alternative fluids for many end users. They find applications in refrigeration and air-conditioning, foam-blowing, general aerosols, solvent cleaning, firefighting, and metered-dose inhaling. They are preferred due to certain physical and chemical characteristics, especially their low toxicity and low flammability. The main sources of atmospheric HFCs are traceable to their sources of application. Two other major emitters are chemical plants making HCFC 22 (where HFC-23 is emitted as a by-product) and HFCs. There are several points in the lifecycle of HFC-using products at which emissions can occur. A computer model uses four emission factors to characterize the HFC emissions, namely fluid manufacturing, product manufacturing, product life, and disposal loss factors. Examples of HFCs include trifluoromethane (HFC-23), difluoromethane (HFC-32), fluoromethane (HFCHydrofluorocarbons 41), 2-chloro-1,1,1,2-tetrafluoroethane (HFC-124), 1,1,2,2,2-pentafluoroethane (HFC-125), 1,1,2,2-tetrafluoroethane (HFC-134), 1,1,1,2-tetrafluoroethane (HFC-134a,), 1,1-difluoroethane (HFC-152a), 1,1,1,2,3,3,3-heptafluoropropane (HFC-227ea).
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.087 | 0.034 |
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".