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Record W2150531251 · doi:10.1029/1999gl011227

Modeling recent climate variability in the Arctic Ocean

2000· article· en· W2150531251 on OpenAlexaboutno aff
Wieslaw Maslowski, B. Newton, Peter Schlösser, Albert J. Semtner, Douglas G. Martinson

Bibliographic record

VenueGeophysical Research Letters · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsClimatologyThermohaline circulationArctic sea ice declineSea iceNorthern HemisphereArctic dipole anomalyArctic ice packForcing (mathematics)Arctic geoengineeringArcticGeologyAtmospheric circulationCanada BasinArctic oscillationOcean currentClimate modelEnvironmental scienceNorth Atlantic oscillationOceanographyClimate changeDrift ice

Abstract

fetched live from OpenAlex

Dramatic changes in the circulation of sea ice and the upper layers of the Arctic Ocean have been reported during the last decade. Similar variability is modeled using a regional, coupled ice‐ocean model. Realistic atmospheric forcing fields for 1979–93 are the only interannual signal prescribed in the model. Our results show large‐scale changes in sea ice and oceanic conditions when comparing results for the late 1970s/early 1980s and the 1990s. We hypothesize that these changes are in response to even larger scale atmospheric variability in the Northern Hemisphere that can be defined as either the Arctic Oscillation or the North Atlantic Oscillation. Agreement between the direction and scale of change in the model and observations, in the absence of interannual forcing from the global ocean thermohaline circulation, suggests that the atmospheric variability by itself is sufficient to produce basin‐scale changes in the Arctic Ocean and sea ice system.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.280
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

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

Citations121
Published2000
Admission routes1
Has abstractyes

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