Bibliographic record
Abstract
Abstract. Launched aboard the Canadian satellite SCISAT in August 2003, the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) instrument has been measuring solar absorption spectra in the ultraviolet (UV) and visible part of the spectrum for more than 20 years. The UV channel measurements from MAESTRO are used to retrieve profiles of ozone from the short-wavelength end of the Chappuis band (UV-ozone) and NO2, while measurements made in the visible part of the spectrum are used to retrieve a separate ozone (Vis.-ozone) product. The latest ozone and NO2 profile products, version 4.5, have been released, which nominally cover the period from February 2004 to December 2023. Due to the buildup of an unknown contaminant, the UV-ozone and NO2 products are only viable up to June 2009 for NO2 and December 2009 for UV-ozone. This study presents comparisons of the version 4.5 MAESTRO ozone and NO2 measurements with coincident, both spatially and temporally, measurements from an ensemble of 11 other satellite limb-viewing instruments. In the stratosphere, the Vis.-ozone product was found to possess a small high bias, with stratosphere averaged relative differences between 2.3 % and 8.2 %, but overall good agreement with the comparison datasets is found. A similar bias, albeit with slightly poorer agreement, is found with the UV-ozone product in the stratosphere, with the average stratospheric agreement between MAESTRO and the other datasets ranging from 2.9 % to 11.9 %. For NO2, general agreement with the comparison datasets is only found in the range from 20 to 40 km. Within this range, MAESTRO is found to have a low bias for NO2, and most of the datasets agree to within 27.5 %, although the average agreement ranges from 8.5 % to 43.4 %.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.015 | 0.007 |
| Insufficient payload (model declined to judge) | 0.463 | 0.338 |
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".