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Record W3114051622 · doi:10.1175/bams-d-19-0281.1

The Inner-Shelf Dynamics Experiment

2020· article· en· W3114051622 on OpenAlexfundno aff
Nirnimesh Kumar, James A. Lerczak, Tongtong Xu, Amy F. Waterhouse, Jim Thomson, Eric Terrill, Christy Swann, Sutara H. Suanda, Matthew S. Spydell, Pieter Smit, Alexandra Simpson, Roland Romeiser, Stephen D. Pierce, Tony de Paolo, André Palóczy, Annika O’Dea, Lisa Nyman, James N. Moum, Melissa Moulton, Andrew M. Moore, Arthur J. Miller, Ryan Mieras, Sophia Merrifield, Kendall Melville, Jacqueline M. McSweeney, Jamie MacMahan, Jennifer MacKinnon, Björn Lund, Emanuele Di Lorenzo, Luc Lenain, Michael Kovatch, T. T. Janssen, Sean Haney, Merrick C. Haller, Kevin Haas, D. J. Grimes, Hans C. Graber, Matt K. Gough, David Fertitta, Falk Feddersen, Christopher A. Edwards, William R. Crawford, John A. Colosi, C. Chris Chickadel, Sean Celona, Joseph Calantoni, Edward F. Braithwaite, Johannes Becherer, John A. Barth, Seongho Ahn

Bibliographic record

VenueBulletin of the American Meteorological Society · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersUniversity of California, San DiegoInnovation, Science and Economic Development CanadaOffice of Naval ResearchUniversity of WashingtonNational Aeronautics and Space Administration
KeywordsOceanographyStratification (seeds)ShoreGeologySubmarine pipelineOcean currentEnvironmental scienceCirculation (fluid dynamics)ClimatologyMeteorologyGeography

Abstract

fetched live from OpenAlex

Abstract The inner shelf, the transition zone between the surfzone and the midshelf, is a dynamically complex region with the evolution of circulation and stratification driven by multiple physical processes. Cross-shelf exchange through the inner shelf has important implications for coastal water quality, ecological connectivity, and lateral movement of sediment and heat. The Inner-Shelf Dynamics Experiment (ISDE) was an intensive, coordinated, multi-institution field experiment from September–October 2017, conducted from the midshelf, through the inner shelf, and into the surfzone near Point Sal, California. Satellite, airborne, shore- and ship-based remote sensing, in-water moorings and ship-based sampling, and numerical ocean circulation models forced by winds, waves, and tides were used to investigate the dynamics governing the circulation and transport in the inner shelf and the role of coastline variability on regional circulation dynamics. Here, the following physical processes are highlighted: internal wave dynamics from the midshelf to the inner shelf; flow separation and eddy shedding off Point Sal; offshore ejection of surfzone waters from rip currents; and wind-driven subtidal circulation dynamics. The extensive dataset from ISDE allows for unprecedented investigations into the role of physical processes in creating spatial heterogeneity, and nonlinear interactions between various inner-shelf physical processes. Overall, the highly spatially and temporally resolved oceanographic measurements and numerical simulations of ISDE provide a central framework for studies exploring this complex and fascinating region of the ocean.

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)0.001
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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

Citations23
Published2020
Admission routes1
Has abstractyes

Explore more

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