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Record W1994822469 · doi:10.1002/asl.305

The West African climate system: a review of the AMMA model inter‐comparison initiatives

2011· review· en· W1994822469 on OpenAlexaff
Paolo Ruti, J. E. Williams, F. Hourdin, Françoise Guichard, Aaron Boone, P. van Velthoven, Florence Favot, Ionela Musat, Markku Rummukainen, Marta Domínguez, Μiguel Angel Gaertner, J. P. Lafore, Teresa Losada, Belén Rodríguez‐Fonseca, Jan Polcher‬, Filippo Giorgi, Yongkang Xue, Idir Bouarar, Kathy S. Law, B. Josse, Brice Barret, Xin Yang, C. Mari, A. K. Traore

Bibliographic record

VenueAtmospheric Science Letters · 2011
Typereview
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsImpact
FundersNatural Environment Research CouncilEuropean CommissionSight Research UKLangley Research CenterNational Aeronautics and Space Administration
KeywordsClimatologyClimate modelMonsoonEnvironmental scienceMultidisciplinary approachTroposphereClimate changeAtmosphere (unit)GeographyMeteorologyGeologyPolitical scienceOceanography

Abstract

fetched live from OpenAlex

Abstract We review the African Monsoon Multidisciplinary Analysis (AMMA) model inter‐comparison activities for West Africa. The Model Inter‐comparison Project is an evaluation exercise of how global and regional atmospheric models represent seasonal and intra‐seasonal variations of the climate and rainfall over the Sahel. The Land surface Model Inter‐comparison Project in turn focuses on modelling critical land surface processes over West Africa and on their link with the atmosphere. The CHEmistry Model Inter‐comparison Project (CHEMIP) is a comparison of the tropospheric composition as simulated by a number of Chemical Transport Models (CTM) and Chemistry‐Climate Models. We highlight the main model limitations and provide recommendations for future development. Copyright © 2011 Royal Meteorological Society

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.047
GPT teacher head0.298
Teacher spread0.251 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations62
Published2011
Admission routes1
Has abstractyes

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