New and improved infrared absorption cross sections for chlorodifluoromethane (HCFC-22)
Bibliographic record
Abstract
Abstract. The most widely used hydrochlorofluorocarbon (HCFC) commercially since the 1930s has been chlorodifluoromethane, or HCFC-22, which has the undesirable effect ofdepleting stratospheric ozone. As this molecule is currently being phased out under the Montreal Protocol, monitoring its concentration profiles using infrared sounders cruciallyrequires accurate laboratory spectroscopic data. This work describes new high-resolution infrared absorption cross sections of chlorodifluoromethane over the spectral range 730 – 1380 cm−1, determined from spectra recorded using a high-resolution Fourier transform spectrometer (Bruker IFS 125HR) and a 26-cm-pathlength cell. Spectra of chlorodifluoromethane/dry synthetic air mixtures were recorded at resolutions between 0.01and 0.03 cm−1 (calculated as 0.9/MOPD; MOPD = maximum optical path difference) over a range of temperatures and pressures (7.5–762 Torr and 191–295 K) appropriate for atmospheric conditions. This new cross-section dataset improves upon the one currently available in the HITRAN and GEISA databases; in particular it provides coverage over a wider range of pressures and temperatures, has more accurate wavenumber scales, more consistent integrated band intensities, improved signal-to-noise, is free of channel fringing, and additionally covers the v2 and v7 bands.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.008 | 0.004 |
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".