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Record W2502482728 · doi:10.1134/s1028334x16070229

Anomalously deep convection in the Irminger Sea during the winter of 2014–2015

2016· article· en· W2502482728 on OpenAlexaboutno aff
С. В. Гладышев, V. S. Gladyshev, S. K. Gulev, Alexey Sokov

Bibliographic record

VenueDoklady Earth Sciences · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsGeologyThermohaline circulationOceanographyAnticycloneSalinityConvectionDeep convectionStructural basinClimatologyTemperature salinity diagramsMeteorologyPaleontologyGeography

Abstract

fetched live from OpenAlex

The anomalous thermohaline properties of the core of the Labrador Sea water (LSW), a product of winter convection resulted from the ocean–winter interaction, which were recorded in the Irminger Sea in 2014 and 2015, are discussed. It is found that, in the summer of 2015, the LSW filled the entire deepwater basin in the south of the sea down to a depth of 1300 m over the periphery of the Irminger gyral, and down to a depth of 1800 m, in the anticyclone eddy formed in early June of 2015. The maximum density of the LSW core here was 27.75 σ θ . Such deep and intense winter convection in the Irminger Sea was last recorded 20 years ago. As a result, the temperature of the LSW dropped to values observed in the years 2002 and 2007, but its average salinity remained high. The LSW that have been formed in recent years are reported to have great amplitude and nonmonotonic variability of the properties.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.207
Teacher spread0.199 · 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

Citations20
Published2016
Admission routes1
Has abstractyes

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