Studies for the Odin sub-millimetre radiometer: III. Performance simulations
Bibliographic record
Abstract
Odin is a small, low-cost satellite with a combined astronomical and aeronomical mission. The mission is divided on an equal basis between astronomy and aeronomy. The aeronomy objectives can be divided into four main subjects: stratospheric ozone chemistry, mesospheric ozone chemistry, the summer mesopause region, and the coupling between atmospheric regions. The primary instrument on Odin is the millimetre and sub-millimetre radiometer (SMR), which is used both for astronomy and aeronomy. It is the first satellite to use sub-millimetre frequencies for limb-sounding mode. Odin is also equipped with an optical spectrometer (OSIRIS). This paper is the third of a three-part series and describes the choices of observing modes and the expected performance of the SMR instrument for the aeronomy mission. The relevant frequencies are identified and the exact selection of lines is made. This is followed by a detailed simulation study to determine the achievable altitude coverage together with the corresponding vertical resolution for each retrievable species. An indication of the expected uncertainties is also given, showing, for example, a high-sensitivity to mesospheric water vapour and stratospheric chlorine monoxide. However, a complete analysis of observation uncertainties must await launch and the completion of the validation programme. PACS Nos.: 42.68A, 07.07D, 07.57K
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".