Technical Note: A trace gas climatology derived from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer dataset
Bibliographic record
Abstract
Abstract. The Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) aboard the Canadian satellite SCISAT (launched in August 2003) was designed to investigate the composition of the upper troposphere, stratosphere, and mesosphere. ACE-FTS utilizes solar occultation to measure temperature and pressure as well as vertical profiles of over thirty chemical species including O3, H2O, CH4, N2O, CO, NO, NO2, N2O5, HNO3, HCl, ClONO2, CCl3F, CCl2F2, and HF. Global coverage for each species is obtained approximately over a three month period and measurements are made with a vertical resolution of typically 3–4 km. A quality-controlled climatology has been created for each of these 14 baseline species, where individual profiles are averaged over the period of February 2004 to February 2009. Measurements used are from the ACE-FTS version 2.2 data set including updates for O3 and N2O5. The climatological fields are provided on a monthly and three-monthly basis (DJF, MAM, JJA, SON) at 5 degree latitude and equivalent latitude spacing and on 28 pressure surfaces (26 of which are defined by the Stratospheric Processes And their Role in Climate (SPARC) Chemistry Climate Model validation activity). The ACE-FTS climatological dataset is available through the ACE website.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.011 |
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".