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Record W2898039682 · doi:10.1038/s41598-018-33640-3

Contribution of hurricane-induced sediment resuspension to coastal oxygen dynamics

2018· article· en· W2898039682 on OpenAlexaff
Laura Bianucci, Karthik Balaguru, Richard W. Smith, L. Ruby Leung, Julia M. Moriarty

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsFisheries and Oceans Canada
FundersPacific Northwest National LaboratoryU.S. Department of EnergyLaboratory Directed Research and DevelopmentNational Oceanic and Atmospheric AdministrationBattelleU.S. Geological Survey
KeywordsWater columnOceanographySedimentContinental shelfEnvironmental scienceSeabedGeologyHydrology (agriculture)Geomorphology

Abstract

fetched live from OpenAlex

Hurricanes passing over the ocean can mix the water column down to great depths and resuspend massive volumes of sediments on the continental shelves. Consequently, organic carbon and reduced inorganic compounds associated with these sediments can be resuspended from anaerobic portions of the seabed and re-exposed to dissolved oxygen (DO) in the water column. This process can drive DO consumption as sediments become oxidized. Previous studies have investigated the effect of hurricanes on DO in different coastal regions of the world, highlighting the alleviation of hypoxic conditions by extreme winds, which drive vertical mixing and re-aeration of the water column. However, the effect of hurricane-induced resuspended sediments on DO has been neglected. Here, using a diverse suite of datasets for the northern Gulf of Mexico, we find that in the few days after a hurricane passage, decomposition of resuspended shelf sediments consumes up to a fifth of the DO added to the bottom of the water column during vertical mixing. Despite uncertainty in this value, we highlight the potential significance of this mechanism for DO dynamics. Overall, sediment resuspension likely occurs over all continental shelves affected by tropical cyclones, potentially impacting global cycles of marine DO and carbon.

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)0.001
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 score0.063
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.017
GPT teacher head0.261
Teacher spread0.244 · 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

Citations67
Published2018
Admission routes1
Has abstractyes

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