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Record W1968965993 · doi:10.5194/acpd-8-7883-2008

The CCCma third generation AGCM and its extension into the middle atmosphere

2008· preprint· en· W1968965993 on OpenAlexaboutno aff
John Scinocca, N. A. McFarlane, Mike Lazare, J. Li, David A. Plummer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsAtmosphere (unit)ClimatologyPolar vortexAtmospheric modelGeneral Circulation ModelNorthern HemisphereClimate modelEnvironmental scienceMeteorologyAtmospheric sciencesStratosphereClimate changeGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

Abstract. The Canadian Centre for Climate Modelling and Analysis third generation atmospheric general circulation model (AGCM3) is described. The discussion summarizes the details of the complete physics package emphasizing the changes made relative to the second generation version of the model. AGCM3 is the underlying model for applications which include the IPCC fourth assessment, coupled atmosphere-ocean seasonal forecasting, the first generation of the CCCma earth system model (CanESM1), and middle-atmosphere chemical-climate modelling (CCM). Here we shall focus on issues related to an upwardly extended version of AGCM3, the Canadian Middle-Atmosphere Model (CMAM). The CCM version of CMAM participated in the 2006 WMO/UNEP Scientific Assessment of Ozone Depletion and issues concerning its climate such as the impact of gravity-wave drag, the modelling of a spontaneous QBO, and the seasonality of the breakdown of the Southern Hemisphere polar vortex are discussed here.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.804
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.040
GPT teacher head0.223
Teacher spread0.184 · 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

Citations173
Published2008
Admission routes1
Has abstractyes

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