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Record W3080911893 · doi:10.1038/s41597-020-00578-z

Arctic tidal current atlas

2020· article· en· W3080911893 on OpenAlexaff
Till M. Baumann, Igor V. Polyakov, Laurie Padman, Seth L. Danielson, Ilker Fer, Markus Janout, William J. Williams, Andrey V. Pnyushkov

Bibliographic record

VenueScientific Data · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsFisheries and Oceans Canada
FundersNorges ForskningsrådBundesministerium für Bildung und ForschungNational Science Foundation
KeywordsBaroclinityCurrent (fluid)OceanographyArcticTidal powerEnvironmental scienceOcean currentSubmarine pipelineTidal rangeClimatologyGeologyEstuaryEcology

Abstract

fetched live from OpenAlex

Tidal and wind-driven near-inertial currents play a vital role in the changing Arctic climate and the marine ecosystems. We compiled 429 available moored current observations taken over the last two decades throughout the Arctic to assemble a pan-Arctic atlas of tidal band currents. The atlas contains different tidal current products designed for the analysis of tidal parameters from monthly to inter-annual time scales. On shorter time scales, wind-driven inertial currents cannot be analytically separated from semidiurnal tidal constituents. Thus, we include 10-30 h band-pass filtered currents, which include all semidiurnal and diurnal tidal constituents as well as wind-driven inertial currents for the analysis of high-frequency variability of ocean dynamics. This allows for a wide range of possible uses, including local case studies of baroclinic tidal currents, assessment of long-term trends in tidal band kinetic energy and Arctic-wide validation of ocean circulation models. This atlas may also be a valuable tool for resource management and industrial applications such as fisheries, navigation and offshore construction.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.076
GPT teacher head0.252
Teacher spread0.176 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations28
Published2020
Admission routes1
Has abstractyes

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