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Record W4321495536 · doi:10.5194/egusphere-egu23-1821

Deep Ocean Circulation in the Subpolar North Atlantic Observed by Acoustically-tracked Floats

2023· preprint· en· W4321495536 on OpenAlexaboutno aff
Sijia Zou, Amy S. Bower, M. Susan Lozier, Heather Furey

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyOceanographyBoundary currentSubmarine pipelineRidgeNorth Atlantic Deep WaterCurrent (fluid)Deep seaGulf StreamStructural basinOcean currentClimatologyDeep waterGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

As part of the Overturning in the Subpolar North Atlantic Program, 122 acoustically-tracked subsurface floats were deployed at 1800-2800 dbar to understand the deep ocean circulation in the subpolar North Atlantic. Gridded mean velocity and eddy kinetic energy (EKE) maps have been constructed using velocity vectors derived from the floats. The mean velocity field reveals a relatively strong deep boundary current around Greenland and in the Labrador Sea, with a weaker deep boundary current over the eastern flank of the Reykjanes Ridge, and near-zero mean flow over the western flank, implying a discontinuous deep boundary current across the subpolar basin. Over most of the subpolar basin, deep EKE resembles that at surface, albeit with smaller magnitudes. A surprising finding about deep EKE is an elevated EKE band east of Greenland. This high EKE band is possibly attributed to the combined influence from propagating Denmark Strait Overflow Cyclones, variability of the wind-driven recirculation offshore of southeast Greenland, and/or topographic waves. The float-based flow fields constructed in this study provide an unprecedented view on the kinematic properties of the large-scale deep circulation in the subpolar North Atlantic.

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 score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.034
GPT teacher head0.216
Teacher spread0.183 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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