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Record W2911252879 · doi:10.1134/s0001433818090086

Steric Level Fluctuations and Deep Convection in the Labrador and Irminger Seas

2018· article· en· W2911252879 on OpenAlexaboutno aff
Т. В. Белоненко, Aleksandr M. Fedorov

Bibliographic record

VenueIzvestiya Atmospheric and Oceanic Physics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsSteric effectsAltimeterGeologyClimatologyOceanographyDeep convectionConvectionSea levelGeodesyGeographyMeteorologyChemistry

Abstract

fetched live from OpenAlex

Abstract The paper considers steric level fluctuations in the northern Atlantic Ocean. We use a method that combines AVISO altimetry and GRACE gravity measurements to evaluate steric level fluctuations and obtain estimates of steric variations in the Labrador and Irminger seas for 2003–2015. The range of steric fluctuations in the Labrador Sea is from –11 to 10 cm, and in the Irminger Sea is from –11 to 12 cm. We estimate trends of steric fluctuations, which indicate a significant increase in the steric component of variability in the level of the North Atlantic. We propose a method for determining regions of deep convection in the Labrador and Irminger seas based on the minimum values of the steric level anomalies (the seasonal component has been excluded) from combined satellite measurement data. Possible spots of deep convection are determined in the Labrador and Irminger seas and shown on steric level fluctuation maps for different years. We demonstrate that deep convection was not manifested in the Labrador Sea in 2006, and there was a general weakening in deep convection processes in the North Atlantic after 2008.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.028
GPT teacher head0.221
Teacher spread0.193 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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