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Record W2950314639 · doi:10.1139/anc-2018-0008

A modeling study on tides in the Port of Vancouver

2019· article· en· W2950314639 on OpenAlexaffabout
Yongsheng Wu, Charles G. Hannah, Mitchell O’Flaherty-Sproul, Phillip MacAulay, Shiliang Shan

Bibliographic record

VenueAnthropocene Coasts · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsRoyal Military College of CanadaFisheries and Oceans CanadaBedford Institute of Oceanography
Fundersnot available
KeywordsAdvectionGeologyMomentum (technical analysis)Circulation (fluid dynamics)HarbourAsymmetryPressure gradientResidualOceanographyTidal ModelClimatologyPhysicsMechanics

Abstract

fetched live from OpenAlex

Abstract In the present paper, tides in the port of Vancouver Harbour have been investigated with a high-resolution three-dimensional hydrodynamic model based on FVCOM (Finite Volume Community Ocean Model). The model was evaluated against field observations including tidal elevations and tidal currents, and the evaluation showed that the model was in good agreement with the observational data. Using the model, we first investigated the horizontal distributions of tides, tidal currents, and tidally induced residual circulation, and then investigated the tidal asymmetry and dynamic mechanisms of tidal flows in the harbour. The tidal residual circulation shows a strong spatial pattern, which is associated with the local coastlines and variation of topography. The tidal asymmetry in the harbour is caused by different mechanisms, not only including the traditional factors, such as residual flows, the interaction between M 2 and its overtide M 4 , but also the interaction of principal astronomical tides of O 1 , K 1 , and M 2 . The momentum balance is dominated by terms of the advection and the pressure gradient in First Narrows and Second Narrows, whereas terms of the local acceleration and the Coriolis are also important in the central harbour. The spatial variations of the momentum terms are strongly associated with the local changes in coastline and topography.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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.

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

Citations10
Published2019
Admission routes2
Has abstractyes

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