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Record W1978861136 · doi:10.1029/2004je002354

A new model for multiscale modeling of the Martian atmosphere, GM3

2005· article· en· W1978861136 on OpenAlexaffabout
Y. Moudden, J. C. McConnell

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsYork University
Fundersnot available
KeywordsMars Exploration ProgramAtmosphere (unit)MartianAtmosphere of MarsAtmospheric modelClimate modelRadiative transferEnvironmental scienceAtmospheric modelsMeteorologyPhysicsRemote sensingGeologyAstrobiologyClimate change

Abstract

fetched live from OpenAlex

A new global model for the Martian atmosphere with a vertical domain extending from the surface into the thermosphere (at about 160–180 km) is presented with some preliminary results. The model is a grid point model with a semi‐Lagrangian semi‐implicit dynamical scheme that is used for weather forecasting by the Meteorological Service of Canada. The physics includes a comprehensive radiative transfer scheme for heating, a boundary and surface layer parameterization. The design of the model allows for different grid configurations that include a globally uniform grid as well as the possibility of zooming over an area of interest with a locally uniform grid. The performance of the model is shown both in global uniform‐resolution simulations as well as high‐resolution simulations over the Tharsis Montes region. The simulated temperatures are compared with the Thermal Emission Spectrometer's measured profiles and the Mars Pathfinder entry data. Both the agreement with the data and the depiction of known features of the Martian atmosphere indicate that the Global Mars Multiscale Model has a good potential for modeling the atmosphere of Mars.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.053
GPT teacher head0.323
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations63
Published2005
Admission routes2
Has abstractyes

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