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Record W2162428985 · doi:10.1029/2005gl023740

One more step toward a warmer Arctic

2005· article· en· W2162428985 on OpenAlexaffabout
Igor V. Polyakov, Agnieszka Beszczyńska-Möller, Eddy C. Carmack, Igor Dmitrenko, Eberhard Fahrbach, И. Е. Фролов, Rüdiger Gerdes, Edmond Hansen, Jürgen Holfort, Vladimir Ivanov, Mark A. Johnson, Michael Kärcher, Frank Kauker, J. Morison, Kjell Arild Orvik, Ursula Schauer, Harper L. Simmons, Øystein Skagseth, Vladimir Sokolov, Michael Steele, Leonid Timokhov, David Walsh, John E. Walsh

Bibliographic record

VenueGeophysical Research Letters · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsFisheries and Oceans Canada
FundersOffice of Naval ResearchNational Science Foundation
KeywordsArcticArctic dipole anomalyOceanographyGeologyClimatologyThe arcticStructural basinCanada BasinLatitudeArctic sea ice declineNorwegianAnomaly (physics)PolarArctic ice packPaleontologyDrift ice

Abstract

fetched live from OpenAlex

This study was motivated by a strong warming signal seen in mooring‐based and oceanographic survey data collected in 2004 in the Eurasian Basin of the Arctic Ocean. The source of this and earlier Arctic Ocean changes lies in interactions between polar and sub‐polar basins. Evidence suggests such changes are abrupt, or pulse‐like, taking the form of propagating anomalies that can be traced to higher‐latitudes. For example, an anomaly found in 2004 in the eastern Eurasian Basin took ∼1.5 years to propagate from the Norwegian Sea to the Fram Strait region, and additional ∼4.5–5 years to reach the Laptev Sea slope. While the causes of the observed changes will require further investigation, our conclusions are consistent with prevailing ideas suggesting the Arctic Ocean is in transition towards a new, warmer state.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.002

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 head0.039
GPT teacher head0.289
Teacher spread0.250 · 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 designObservational
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

Citations402
Published2005
Admission routes2
Has abstractyes

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