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Record W2585681908 · doi:10.1002/2016jc012391

Winter to summer oceanographic observations in the <scp>A</scp>rctic <scp>O</scp>cean north of <scp>S</scp>valbard

2017· article· en· W2585681908 on OpenAlexaboutno aff
Amélie Meyer, Arild Sundfjord, Ilker Fer, Christine Provost, Nicolás Villacieros‐Robineau, Zoé Koenig, Ingrid H. Onarheim, Lars H. Smedsrud, Pedro Duarte, Paul A. Dodd, Robert M. Graham, Sunke Schmidtko, Hanna M. Kauko

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsPlateau (mathematics)GeologyOceanographyArctic ice packArcticMixed layerSea iceThe arcticCanada BasinClimatologyStructural basinGeomorphology

Abstract

fetched live from OpenAlex

Abstract Oceanographic observations from the Eurasian Basin north of Svalbard collected between January and June 2015 from the N‐ICE2015 drifting expedition are presented. The unique winter observations are a key contribution to existing climatologies of the Arctic Ocean, and show a ∼100 m deep winter mixed layer likely due to high sea ice growth rates in local leads. Current observations for the upper ∼200 m show mostly a barotropic flow, enhanced over the shallow Yermak Plateau. The two branches of inflowing Atlantic Water are partly captured, confirming that the outer Yermak Branch follows the perimeter of the plateau, and the inner Svalbard Branch the coast. Atlantic Water observed to be warmer and shallower than in the climatology, is found directly below the mixed layer down to 800 m depth, and is warmest along the slope, while its properties inside the basin are quite homogeneous. From late May onwards, the drift was continually close to the ice edge and a thinner surface mixed layer and shallower Atlantic Water coincided with significant sea ice melt being observed.

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)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.067
GPT teacher head0.313
Teacher spread0.246 · 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 teacher head, not a consensus.

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

Citations74
Published2017
Admission routes1
Has abstractyes

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