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Record W2808980927 · doi:10.1029/2018jc013770

Tidally Modulated Internal Hydraulic Flow and Energetics in the Central Canadian Arctic Archipelago

2018· article· en· W2808980927 on OpenAlexafffundabout
Kenneth Hughes, Jody Klymak, William J. Williams, Humfrey Melling

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsFisheries and Oceans CanadaUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationArcticNet
KeywordsBarotropic fluidIsopycnalSillHydraulic jumpInternal waveBaroclinityThermoclineArchipelagoInternal tideOutflowGeologyKelvin waveArcticAdvectionTidal powerOceanographyFlow (mathematics)ClimatologyMechanicsPhysics

Abstract

fetched live from OpenAlex

Abstract The Canadian Arctic Archipelago is a key conduit for comparatively fresh Arctic waters flowing to the Atlantic. Model estimates of the freshwater outflow, which is strongly correlated with the volume flux, contain major uncertainties because most existing models exclude tides, marginally resolve the internal Rossby radius, or both. At the same time, barotropic tidal models preclude stratified flow effects. Here we assess the relative importance of barotropic and baroclinic processes to water mass transformation, friction, and energy losses motivated by processes observed in a fine‐scale survey in the central Archipelago. A sharp separation of warmed Canada Basin water and locally formed water is observed over a long sill in a narrow channel and coincides with an internal hydraulic jump caused by the mean flow. Tidal currents, however, modulate the jump, as demonstrated by both scale analysis and a two‐dimensional simulation. The jump, together with internal tides propagating as Kelvin waves, leads to isopycnal displacements up to 50 m. The generation of these internal Kelvin waves has a leading‐order role in a regional energy budget. It is small, however, relative to bottom boundary layer dissipation, which accounts for an estimated 50% of the total tidal energy losses. Consequently, adding tides needs to be a priority for regional models.

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 score0.032
Threshold uncertainty score0.087

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 studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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

Citations14
Published2018
Admission routes3
Has abstractyes

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