The MAESTRO Spectrophotometer on Canada’s SCISAT satellite: Advances in data processing and improved data products
Bibliographic record
Abstract
The ACE-FTS and MAESTRO instruments have now been operating on the Canadian Space Agency’s SCISAT satellite as the Atmospheric Chemistry Experiment (ACE) for nearly 20 years. The ACE satellite is approximately 1 m in diameter and 1 m deep and has a mass of 150 kg. The Measurement of Aerosol in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) spectrophotometer continues to measure ozone, water vapour and aerosol in the stratosphere and upper troposphere. Like the ACE‑FTS, MAESTRO delivers results from nearly 30 occultation measurements per day, but with a higher vertical resolution of just over 1 km over a range as large as 5 to 40 km as meteorological conditions allow. It measures from 500 nm to 1000 nm with a resolution of 1 to 2 nm. The instrument design and performance will be briefly discussed and the algorithms developed to process the data and deal with peculiarities in the performance of the satellite will be described. Significant progress has been made recently in improving the retrievals that has resulted in improved accuracy and a larger number of successful retrievals at lower altitudes. A new dataset with these improvements will be available for other researchers. Some examples which illustrate the improvements will be presented.The ACE satellite was funded by the Canadian Space Agency (CSA) and launched by NASA. The CSA funds the MAESTRO data processing. Environment Canada (EC) partly funded the construction of the MAESTRO instrument.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.012 |
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".