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Record W3209247797

MODELLING COASTAL PROCESSES DRIVEN BY WINDS AND TIDES ACROSS A RANGE OF SPATIAL SCALES IN A MACROTIDAL BAY

2021· dissertation· en· W3209247797 on OpenAlexfundno aff
Cody Mclaughlin

Bibliographic record

VenueQSpace (Queen's University Library) · 2021
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaQueen's UniversityDalhousie University
KeywordsBayOceanographyRange (aeronautics)GeologyClimatologyTemporal scalesGeographyEnvironmental scienceEngineeringEcology
DOInot available

Abstract

fetched live from OpenAlex

The Bay of Fundy system in the Atlantic Ocean is a highly dynamic environment characterized by the highest tidal range in the world. The area contains a wide range of coastal environments and structures including salt marshes and protective dyke systems. These systems are at risk of being altered due to future climate change, with likely increases in mean sea level and storm intensity, and proposed installation of in-stream tidal power extraction devices. To assess the vulnerability of the Bay of Fundy to hazards, large-scale and small-scale investigations are completed using available field observations and the hydrodynamic model Delft3D. The large-scale investigation composed of examining the effects of hurricane induced storm surge in the Gulf of Maine and Bay of Fundy using a depth-averaged model and two connected model grids. Hurricane Arthur (2014) is used as a test storm to validate the model before varying input conditions were used including modelling the Saxby Gale of 1869, a devastating storm that impacted the Bay of Fundy. Model results suggest that the combined effects of wind driven waves and storm surge could overtop dyke systems in the Minas Basin if the storm coincides with the high tide of a perigean spring tide. The small-scale investigation is focused on Kingsport Marsh, Nova Scotia, an intertidal salt marsh in the Minas Basin, using a three-dimensional model and four connected model grids with increasing resolution. The goal of this study is to gain insight to the hydrodynamics and morphology of the marsh channels and mudflats. Observational results over a 7-year time period suggest that the bed is slowly accreting in the marsh and that the networks of creek channels are migrating. Model results are validated at the two instrument sites and the model is used to spatially analyze the intertidal hydrodynamics. Spatial model results display a dynamic environment during the flood and ebb tides with bed shear stresses sufficient to initiate sediment resuspension. Overall, this research contributed to a better understanding of the coastal processes in a highly dynamic macrotidal environment, by aiding in the understanding of the complexity of tidal marsh environments as well as assessing the risk involved in storm surge interactions to local dyke systems, needed to accurately predict future responses to storms, climate change and proposed infrastructure development.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.005
GPT teacher head0.174
Teacher spread0.170 · 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 designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

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