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Record W2138290588 · doi:10.1029/2012jc008234

Shoaling of the nutricline with an increase in near‐freezing temperature water in the Makarov Basin

2012· article· en· W2138290588 on OpenAlexaffabout
Shigeto Nishino, Motoyo Itoh, William J. Williams, Igor Semiletov

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsFisheries and Oceans Canada
FundersJST-Mirai ProgramJapan Agency for Marine-Earth Science and Technology
KeywordsOceanographyOcean gyreGeologyShoaling and schoolingMeltwaterWater massCircumpolar deep waterSea iceStructural basinDeep waterGeomorphologyNorth Atlantic Deep WaterEcology

Abstract

fetched live from OpenAlex

The water mass changes in the Makarov Basin and adjacent areas associated with the recent loss of Arctic sea ice had not been studied in detail. We combined data obtained from multiple cruises in these regions and used chemical tracers to investigate the spatial and temporal changes in water masses. Our data show that a previously present temperature maximum water has disappeared from the Makarov Basin and Chukchi Abyssal Plain due to enhanced cooling and convection in the East Siberian Sea. In addition, a large volume of water has formed by cooling and convection and is flowing into the Makarov Basin, producing a temperature minimum with relatively high nutrients and resulting in a shoaling of the nutricline. This temperature minimum water likely originated from the eastern part of the East Siberian Sea, where significant open water areas appeared after 2005 in the freeze‐up season. The water mass boundary between this temperature minimum water and the Pacific‐origin temperature minimum water shifted westward from the Chukchi Plateau in the early 2000s to the Mendeleyev Ridge in the late 2000s, probably owing to a westward flow of the enhanced Beaufort Gyre associated with recent sea ice loss in the Canada Basin. Although the shoaling of the nutricline in the Makarov Basin could increase phytoplankton production, such production could decrease in the southern Makarov Basin because a large amount of sea ice meltwater covers that region and might decrease the nutrient supply from the subsurface layer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

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

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 head0.023
GPT teacher head0.282
Teacher spread0.259 · 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

Citations48
Published2012
Admission routes2
Has abstractyes

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