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Record W2136680593 · doi:10.1002/9781118351475.ch9

Climate and Climate‐System Modelling

2013· other· en· W2136680593 on OpenAlexaff
L. D. Danny Harvey

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiosphereCryosphereRadiative forcingEarth system scienceBiosphere modelClimate modelForcing (mathematics)Climate changeEnvironmental scienceEarth scienceClimatologyClimate stateClimate commitmentClimate systemTransient climate simulationMeteorologyGlobal warmingGeologyGeographyEffects of global warmingEcologyOceanographySea ice

Abstract

fetched live from OpenAlex

The climate system consists of the atmosphere, oceans, cryosphere, biosphere, and lithosphere (the Earth's crust). In building computer models of the climate system, there are a number of basic considerations, namely, the number of components to be included and the comprehensiveness of a climate model. The comprehensiveness depends in part on the timescale under consideration. A long-term goal of the climate-research community is the development of increasingly sophisticated models that couple more and more components of the climate system. The online material that accompanies this chapter illustrates basic principles governing changes in climate in response to a radiative forcing, and governs changes in the terrestrial biosphere in response to changes in atmospheric CO2 and temperature. The chapter also outlines the equilibrium and transient calculations for both climate and the terrestrial biosphere that are performed in the online Excel package.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.050
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0500.013

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 head0.006
GPT teacher head0.174
Teacher spread0.168 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations3
Published2013
Admission routes1
Has abstractyes

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