Some features of effective radius and variance of dust particles in numerical simulations of the dust climate on Mars
Bibliographic record
Abstract
Airborne dust is an important constituent in the Martian atmosphere because of its radiative interaction with the atmospheric circulation. Dust size is one crucial factor in determining this effect. In reality dust sizes are varied; however, in numerical modeling of dust processes, dust size has usually been described by choice of a particular size distribution function, or by use of fixed values of effective radius (ER) and effective variance (EV). In this work, we present analytical expressions that have been derived to specify ER and EV for N-bin dust schemes, based on a model-calculated dust mixing ratio. Numerical simulations based on this approach thus would consider the effects of variable ER on the atmospheric radiation and their interaction. Results have revealed some interesting features of the dust distribution parameters, such as seasonal and spatial variation of ER and EV, which are generally consistent with some previous observational and modeling studies. Compared with the usual approach of using a fixed ER, simulation results from the present approach suggest that the variability of ER can have significant effects on the simulated thermal field of the Martian atmosphere.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".