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Record W7055572392

Deep water circulation and composition in the Arctic Ocean by dissolved barium, aluminium and silicate

2012· article· en· W7055572392 on OpenAlexaboutno aff

Bibliographic record

VenueIntegrated Information System (Vlaams Instituut Voor De Zee) · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Frequency and Time Standards
Canadian institutionsnot available
Fundersnot available
KeywordsGeotracesRidgeStructural basinDissolutionArcticWater columnNorth Atlantic Deep WaterBottom waterWater massDeep water
DOInot available

Abstract

fetched live from OpenAlex

As part of the ARK-XXII/2 Polarstern expedition in summer 2007, dissolved Ba was analyzed in the Eurasian Basins and the Makarov Basin including the Alpha and Mendeleyev Ridges as well as on the adjacent shelves. The data was compared with data of dissolved Al and Si from the same cruise. Superimposed on the gradual increase of concentration with depth by dissolution of the particle rain, we observe different flow patterns in intermediate waters along the track. In the Atlantic and Intermediate Depth Water (AIDW) in the Amundsen Basin the influence from Eurasian shelf water can be seen in slightly enhanced concentrations of dissolved Ba compared with Al and Si. At the same time Al concentrations decrease with distance from the Eurasian shelves. Source waters to the Atlantic layer Water (ALW) in the Makarov Basin have the same background Ba concentrations as the Nansen AIDW. We describe the distributions of the elements in the Deep Eurasian and Bottom Water (DEBW) by deep shelf convection as well as diffusion from sediments controlling concentrations in the Nansen DEBW while in the Amundsen DEBW diffusion from sediments appears to be more important. In the Makarov Basin inflow from the Canadian Basin and overflow from the Amundsen Basin at 2000 m depth at the Lomonosov Ridge are required to explain the composition of bottom waters.

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 score0.339
Threshold uncertainty score0.494

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 communication0.0000.002
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 head0.005
GPT teacher head0.213
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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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