Trifluoroiodomethane\nas a Precursor to High Global\nWarming Potential Climate Pollutants: Could the Transformation of\nClimatically Benign CF<sub>3</sub>I into Potent Greenhouse Gases Significantly\nIncrease Refrigerant-Related Greenhouse Gas Emissions?
Bibliographic record
Abstract
The transition away from the production and consumption\nof high\nglobal warming potential (GWP) hydrofluorocarbons (HFCs) under the\n2016 Kigali Amendment to the Montreal Protocol on Substances that\nDeplete the Ozone Layer (Montreal Protocol) has prompted air conditioning,\nrefrigeration, and heat pump equipment manufacturers to seek alternative\nrefrigerants with lower direct climate impacts. Additional factors\naffecting alternative refrigerant choice include safety (i.e., flammability\nand toxicity), environmental, and thermodynamic constraints. At the\nsame time, manufacturers are incentivized to seek refrigerants with\nhigher energy efficiency, which saves on electricity costs and reduces\nindirect greenhouse gas emissions from electricity generation. The\nlife cycle climate performance (LCCP) metric is commonly used to assess\nthe combined direct and indirect climate impacts of refrigerant-use\nequipment. Here, we consider an additional impact on climate performance:\nthe degradation of refrigerant in equipment, i.e., the direct climate\nimpacts of high-GWP byproducts that can form as the result of adding\ntrifluoroiodomethane (CF<sub>3</sub>I) to refrigerant blends to reduce\nflammability. Such a production of high-GWP gases could change the\nacceptability of CF<sub>3</sub>I-containing refrigerants. Further,\nit highlights the need to understand refrigerant degradation within\nequipment in calculations of the environmental acceptability of new\ncooling technology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".