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Record W3082813261

Конвекция и стратификация вод на севере Атлантического океана по данным измерений зимой 2013/14 гг

2017· article· ru· W3082813261 on OpenAlexaboutno aff
Anastasia Falina, Artem Sarafanov, С. А. Добролюбов, V. S. Zapotylko, С. В. Гладышев

Bibliographic record

VenueВестник Московского университета. Серия 5. География · 2017
Typearticle
Languageru
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsOcean gyreGeologyArgoOceanographyStratification (seeds)RidgeConvectionClimatologyWater columnWater massConvective mixingGeographyPaleontologyMeteorologySubtropics
DOInot available

Abstract

fetched live from OpenAlex

Spatial characteristics of oceanic convection in the North Atlantic Subpolar Gyre in winter 2013/14 are investigated basing on the analysis of Argo float data. Domains of the most intense convective mixing are identified by quantifying and mapping the water column vertical stratification. The areas of the Subpolar Mode Water formation are found along the Irminger Current, namely over the northwestern slope of the Reykjanes Ridge and in the vicinity of the Denmark Strait. The location of convection domains and the spatial changes of mixed layer properties in these domains are in a good agreement with a contemporary concept stating the localized formation of the mode waters along each of the individual branches of the North Atlantic Current and the increasing density of the mode waters in the northward direction. The main role in the formation of the Labrador Sea Water belonged to the convection zone in the Labrador Sea, where the mixing depth reached 1750 m for the first time over the past six years. The relatively cold and fresh intermediate waters, matching the Labrador Sea Water in their properties, were also formed in the domain to the south of the Cape Farewell and in the southern part of the Irminger Sea.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.004

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 head0.225
Teacher spread0.208 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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