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Summer freshwater content variability of the upper ocean in the Canada Basin during recent sea ice rapid retreat

2011· article· en· W277599356 on OpenAlexaboutno aff

Bibliographic record

VenueADVANCES IN POLAR SCIENCE · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographyStructural basinGeologySea iceClimatologyPhysical geographyGeographyGeomorphology

Abstract

fetched live from OpenAlex

Freshwater content (<italic>FWC</italic>) in the Arctic Ocean has changed rapidly in recent years, in response to significant decreases in sea ice extent. Research on freshwater content variability in the Canada Basin, the main storage area of fresh water is very important to understand the input-output freshwater in the Arctic Ocean. The <italic>FWC</italic> in the Canada Basin was calculated using data from the Chinese National Arctic Research Expeditions of 2003 and 2008, and from expeditions of the Canadian icebreaker Louis S. St-Laurent (LSSL) from 2004 to 2007. Results show that the upper ocean in the Canada Basin became continuously fresher from 2003 to 2008, except during 2006. The <italic>FWC</italic> increased at a rate of more than 1 m•a<sup>−1</sup>, and the maximum increase, 7 m, was in the central basin compared between 2003 and 2008. Variability of the <italic>FWC</italic> was almost entirely limited to the layer above the winter Bering Sea Water (wBSW), below which the <italic>FWC</italic> remained around 3 m during the study period. Contributors to the <italic>FWC</italic> increase are generally considered to be net precipitation, runoff changes, Pacific water inflow through the Bering Strait, sea ice extent, and the Arctic Oscillation(AO). However, we determined that the first three contributors did not have apparent impact on the <italic>FWC</italic> changes. Therefore, this paper focuses on analysis of the latter two factors and the results indicate that they were the major contributors to the <italic>FWC</italic> variability in the basin.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.204
Teacher spread0.187 · 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.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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