ENANTIOMERIC EXCESS MEASUREMENTS USING MICROWAVE THREE-WAVE MIXING
Bibliographic record
Abstract
Fluorine- and chlorine-containing molecules in the atmosphere are very strong greenhouse gases, meaning that even small amounts of these gases contribute significantly to the radiative forcing of climate. In addition, a number of these molecules, such as chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs), are harmful to the Earth's ozone layer and for this reason their use is regulated by the 1987 Montreal Protocol. The recent Kigali Amendment has added hydrofluorocarbons (HFCs) to the list of controlled substances, coming into effect on 1 January 2019. HFCs, which do not deplete stratospheric ozone, were introduced as refrigerant replacements for CFCs and HCFCs. They are potent greenhouse gases, with global-warming potentials many times greater than carbon dioxide, and are increasing in the atmosphere at a very fast rate. \n\n\n\nA number of satellite instruments, in particular the ACE-FTS (Atmospheric Chemistry Experiment – Fourier Transform Spectrometer), can monitor many of these species by detecting infrared radiation that has passed through the Earth's atmosphere. However, the quantification of their atmospheric abundances crucially requires accurate quantitative infrared spectroscopy. This talk will focus on new and improved laboratory spectroscopic measurements for a number of important halogenated species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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; 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".