Modeled O<sub>2</sub> nightglow distributions in the Venusian atmosphere
Bibliographic record
Abstract
In this paper, we study the global distribution of the O2Infrared Atmospheric (0‐0) emission at 1.27μm in the Venusian atmosphere with an airglow model in combination with atmospheric conditions provided by a three‐dimensional model, the Venus Thermospheric Global Circulation Model. We compare our model simulations with airglow observations of this emission from the Visible and InfraRed Thermal Imaging Spectrometer on board the Venus Express orbiter. Our model is successful in reproducing the latitudinal and temporal trends seen in the observations for latitudes between 0° and 30°, while poleward of 30°, the model results start to diverge away from the measurements. We attribute this discrepancy to the atomic oxygen distribution at these latitudes in our model that is inconsistent with the recent measurements. We also conducted a sensitivity study to explore the dependence of the vertical structure and the distribution of the airglow emission on the atmospheric conditions. The sensitivity study confirms that changes in the distribution of atomic oxygen significantly affect the characteristics of the airglow layer. Therefore, meaningful comparisons with observations require a three‐dimensional model, which accounts for dynamical variations in the background atmosphere. With this investigation, we highlight the impact of the atmospheric conditions on the airglow distribution, which is important for the understanding of how the phenomenon plays.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".