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Record W2208835046 · doi:10.1175/jpo-d-15-0095.1

On the Mediterranean Water Composition

2015· article· en· W2208835046 on OpenAlexaboutno aff
Lidia I. Carracedo, Paula C. Pardo, Susana Flecha, Fı́z F. Pérez

Bibliographic record

VenueJournal of Physical Oceanography · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographyAntarctic Intermediate WaterOutflowWater massEntrainment (biomusicology)Mediterranean climateThermohaline circulationGeologyWater columnNorth Atlantic Deep WaterMediterranean seaCircumpolar deep waterStructural basinSalinityPlumeGeomorphologyGeography

Abstract

fetched live from OpenAlex

Abstract The Mediterranean Outflow Water (MOW) spills from the Mediterranean Sea (east North Atlantic basin) west off the Strait of Gibraltar. As MOW outflows, it entrains eastern North Atlantic Central Waters (ENACW) and Intermediate Waters to form the neutrally buoyant Mediterranean Water (MW) that can be traced over the entire North Atlantic basin. Its high salinity content influences the thermohaline properties of the intermediate–deep water column in the North Atlantic and its dynamics. Here, the composition of MW in its source region (the Gulf of Cádiz, west off Strait of Gibraltar) is investigated on the basis of an optimum multiparameter analysis. The results obtained indicate that mixing of MOW (34.1% ± 0.3%) occurs mainly with overlying ENACW (57.1% ± 0.8%) in a process broadly known as central water entrainment. A diluted form (80% of dilution) of the Antarctic Intermediate Water (AAIW) reaches the region and also takes part in MW formation (8.3% ± 0.5%). Finally, the underlying Labrador Sea Water (LSW) also contributes (0.4% ± 0.1%) to the characteristics of MW. From these results and considering 0.74 Sverdrups (Sv; 1 Sv ≡ 10 6 m 3 s −1 ) as the mean outflow of MOW, the MW exportation rate was inferred (2.2 Sv), which, decomposing MW, means that the MOW outflow is accompanied by 1.24 Sv of entrained ENACW, 0.18 Sv of AAIW, and <0.01 Sv of LSW.

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 score0.606
Threshold uncertainty score0.210

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 head0.020
GPT teacher head0.220
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 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

Citations29
Published2015
Admission routes1
Has abstractyes

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