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Record W2016178350 · doi:10.1029/2008jd010481

A model of dust in the Martian lower atmosphere

2009· article· en· W2016178350 on OpenAlexaff
Richard Davy, Peter A. Taylor, Wensong Weng, P.‐Y. Li

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsYork University
Fundersnot available
KeywordsAtmosphere (unit)Planetary boundary layerLidarDust stormAtmosphere of MarsAtmospheric sciencesMartianMars Exploration ProgramBoundary layerEnvironmental scienceStormMineral dustMartian surfaceOptical depthGeologyPhysicsMeteorologyAstrobiologyAerosolRemote sensingMechanics

Abstract

fetched live from OpenAlex

A coupled boundary layer–Aeolian dust model of the Martian atmosphere is presented. This model was developed to determine how radiation (scattering, absorption, and emission) by dust affects the boundary layer and, in turn, how this affects the dust distribution in the atmosphere. This was achieved by coupling a planetary boundary layer (PBL) model with the 2007 dust model of P. A. Taylor et al. The principle motivation here is to determine whether it will be possible to use the lidar on board the Phoenix lander to detect the depth of the Martian boundary layer from the dust distribution. Runs were conducted for different dust profiles, roughness lengths, and geostrophic winds. These indicate that there should be a distinct horizon in dust concentration which will be detectable by the Phoenix lidar. The model is also applied to the 1977B dust storm optical data of Viking Lander 1, and our analysis indicates a significant improvement over previous 1‐D studies of dust storm decay.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.047
GPT teacher head0.316
Teacher spread0.269 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations21
Published2009
Admission routes1
Has abstractyes

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