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Record W1995144709 · doi:10.1080/07055900.2011.602325

Response of the Pacific Ocean Circulation to Climate Change

2011· article· en· W1995144709 on OpenAlexvenueno aff
Yiyong Luo, Lewis M. Rothstein

Bibliographic record

VenueATMOSPHERE-OCEAN · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersLawrence Livermore National LaboratoryNational Science Foundation
KeywordsOcean gyreThermoclineClimatologyClimate changeEnvironmental scienceOcean heat contentSubtropicsMixed layerOcean currentOceanographySubtropical ridgeSea surface temperatureAbrupt climate changePacific decadal oscillationGlobal warmingEffects of global warmingGeologyPrecipitationGeographyMeteorology

Abstract

fetched live from OpenAlex

The response of the Pacific Ocean circulation to climate change is investigated by comparing solutions from a set of Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled models for a present-day climate (the 20C3M experiments) and a future, warmer climate (the SRESA1B experiments). Under the warmer climate scenario, the oceanic changes in the tropical Pacific include a relatively weak warming of the western equatorial thermocline, a weakening of the surface current system and a complicated change in the structure of the Equatorial Undercurrent (EUC) with an increased flow in its upper branch but a decreased flow in its lower branch. As the climate warms, the North Pacific Ocean features a basin-scale reduction in mixed layer depth, a weakening of the subtropical countercurrent (STCC), a northward shift of the Kuroshio Extension (KE) and an overall slowdown of the subtropical gyre. In the South Pacific, the warmer climate induces significant changes in the upper ocean of the eastern subtropics including a relatively weak warming, a deepening of mixed layer depth and an anticylonic circulation.

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)0.003
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: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.234
Teacher spread0.197 · 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

Citations24
Published2011
Admission routes1
Has abstractyes

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Same venueATMOSPHERE-OCEANSame topicClimate variability and modelsFrench-language works237,207