Pressure/temperature and volume mixing ratio retrievals for the Atmospheric Chemistry Experiment (ACE)
Bibliographic record
Abstract
Scisat-1, otherwise known as the Atmospheric Chemistry Experiment, is a satellite mission designed for remote sensing of the Earth's atmosphere using occultation spectroscopy. The primary goal of the mission is to investigate the chemical and dynamical processes that govern ozone distribution in the stratosphere and upper troposphere. It has been developed under the auspices of the Canadian Space Agency and is scheduled for launch in December of 2002. The primary instrument on board Scisat-1 is a high resolution Fourier transform spectrometer (FTS) operating in the infrared. Pressure and temperature as a function of altitude will be determined from the FTS measurements through analysis of carbon dioxide absorption. Volume mixing ratio (vmr) profiles will be retrieved for more than thirty molecules of atmospheric interest. Both the pressure/temperature and vmr retrievals use non-linear least squares Global Fit type approaches. For the pressure/temperature analysis, several variations are being developed; the choice of which version to implement depends on the quality of the pointing information obtained from the satellite. In the case of poor pointing knowledge, tangent height separations between measurements will be determined directly from the FTS data (simultaneously with the pressure and temperature determination) through the imposition of hydrostatic equilibrium.
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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".