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Record W7011669174

Modelling coastal processes at Shippagan Gully inlet, New Brunswick, Canada

2013· article· en· W7011669174 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2013
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsInletStormStorm surgeSediment transportSedimentary rockCoastal managementTidal rangeNumerical modelsSurge
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the development, calibration and application of a numerical model of the hydrodynamic and sedimentary processes at a dynamic tidal inlet known as Shippagan Gully, located on the Gulf of St-Lawrence near Le Goulet, New Brunswick. The new model has been developed to provide guidance concerning the response of the inlet mouth to various potential interventions aimed at increasing navigation safety. The new model is based on coupling the most recent CMS-Flow and CMSWave models developed by the US Army Corps of Engineers. The coupled model is capable of simulating the depth-averaged currents generated within Shippagan Gully and along the neighbouring coastline due to the effects of tides, winds and waves; the transport of non-cohesive sediments; and the resulting changes in seabed morphology. The development of the model and the steps taken to calibrate and validate it against field measurements are described. The application of the model to predict the coastal processes and the response of the inlet mouth to several storms is described and discussed. The influences of storm direction and storm surge on coastal processes is presented and discussed. The research described herein will contribute to an improved understanding of the hydrodynamics and sedimentary processes at strongly ebb-dominated tidal inlets in general and Shippagan Gully in particular.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.779

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 science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.194
Teacher spread0.177 · 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 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

Citations0
Published2013
Admission routes2
Has abstractyes

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Same venueNPARCSame topicHistory of Computing TechnologiesFrench-language works237,207