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Record W4400985399 · doi:10.1038/s41561-024-01494-2

Highly variable deep-sea currents over tidal and seasonal timescales

2024· article· en· W4400985399 on OpenAlexaff
Lewis Bailey, Michael Clare, James E. Hunt, Ian Kane, Elda Miramontes, Marco Fonnesu, Ricardo Argiolas, G. Malgesini, Régis Wallerand

Bibliographic record

VenueNature Geoscience · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Calgary
FundersNatural Environment Research CouncilSight Research UK
KeywordsSeabedGeologySubmarine pipelineCurrent (fluid)Turbidity currentOceanographyDeep seaSedimentContinental shelfSediment transportBioturbationOcean currentStructural basinGeomorphologySedimentary depositional environment

Abstract

fetched live from OpenAlex

Abstract Deep-sea transport of sediment and associated matter, such as organic carbon, nutrients and pollutants, is controlled by near-bed currents. On the continental slope, these currents include episodic down-slope gravity-driven turbidity currents and more sustained thermohaline-driven along-slope contour currents. Recent advancements in deep-sea monitoring have catalysed a step change in our understanding of turbidity currents and contour currents individually. However, these processes rarely operate in isolation and the near-bed current regime is still to be quantified in a mixed system. Such measurements are crucial for understanding deep-sea particulate transport, calibrating numerical models and reconstructing palaeoflow. Here we use 4 years of observations from 34 instrument moorings in a mixed system offshore of Mozambique to show that near-bed currents are highly dynamic. We observe spatial variability in velocity over tidal and seasonal timescales, including reversals in current direction, and a strong steering and funnelling influence by local seabed morphology. The observed near-bed currents are capable of mobilizing and distributing sediments across the seabed, therefore complicating deep-sea particulate transport and reconstruction of palaeoceanographic conditions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.223
Teacher spread0.218 · 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.

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

Citations19
Published2024
Admission routes1
Has abstractyes

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