The ALTIUS mission
Bibliographic record
Abstract
Abstract. This article outlines the objectives, concept and expected performance of the ALTIUS (Atmospheric Limb Tracker for the Investigation of the Upcoming Stratosphere) mission in view of the continuation of earth limb measurements for atmospheric science. This type of measurement became rare with the failure of the European ENVISAT mission in 2012 and the number will further decrease when several Canadian, Swedish and US limb missions will terminate within the next few years. The project is presented in the frame of a small mission initiative based on a micro-satellite platform of the PROBA (Project for On-Board Autonomy) class, with a high agility allowing for atmospheric limb observations in different remote sensing geometries from a low earth orbit. The instrument consists of three independent spectral imagers covering the UV-Vis-NIR ranges. Recently, the ALTIUS mission has been declared as an element compliant to the ESA Earth Watch programme. The paper identifies the general scientific context of the project and derives the mission, instrument and scientific products requirements. The general design of the payload and platform systems is discussed. The preliminary data processing chain is presented, from telemetry data to retrieved geophysical profiles, with a complementary data assimilation level. A preliminary assessment of the mission performance is discussed with focus on ozone profile retrievals, which are the main objective of the mission.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.021 |
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".