Comparison of HDO measurements from Envisat/MIPAS with observations by Odin/SMR and SCISAT/ACE-FTS
Bibliographic record
Abstract
Abstract. Measurements of thermal emission in the mid-infrared by Envisat/MIPAS allow the retrieval of HDO information roughly in the altitude range between 10 km and 50 km. From June 2002 to March 2004 MIPAS performed measurements in the full spectral resolution mode. To assess the quality of the HDO data set obtained during that period comparisons with measurements by Odin/SMR and SCISAT/ACE-FTS were performed. Comparisons were made on profile-to-profile basis as well as using seasonal and monthly averages. All in all the comparisons yield favourable results. The largest deviations between MIPAS and ACE-FTS are observed below 15 km, where relative deviations can occasionally exceed 100%. Despite these deviations in the absolute amount of HDO the latitudinal structures observed by both instruments are consistent in this altitude range. Between 15 km and 20 km there is less good agreement, in particular in the Antarctic during winter and spring. Also in the tropics some deviations are found. Above 20 km there is a high consistency in the structures observed by all three instruments. MIPAS and ACE-FTS typically agree within 10%, with MIPAS mostly showing higher abundances than ACE-FTS. Both data sets show considerably more HDO than SMR. This bias can be explained basically by uncertainties in spectroscopic parameters. Above 40 km, where the MIPAS HDO retrieval reaches its limits, still good agreement with the structures observed by SMR is found for most seasons. This puts some confidence in the MIPAS data at these altitudes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".