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Record W4392547659 · doi:10.3390/jmse12030461

Hydrodynamic Modeling of Water Renewal Time and Potential Dissolved Matter Using TELEMAC: Applications to Shediac Bay (New Brunswick, Canada)

2024· article· en· W4392547659 on OpenAlexaffabout
Chinh Lieou, Serge Jolicoeur, Thomas Guyondet, Stéphane O’Carroll, Tri Nguyen-Quang

Bibliographic record

VenueJournal of Marine Science and Engineering · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsFisheries and Oceans CanadaUniversité de MonctonDalhousie University
Fundersnot available
KeywordsBayEnvironmental scienceHydrology (agriculture)OceanographyGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

This study examines the hydrodynamic regimes in Shediac Bay, located in New Brunswick, Canada, with a focus on the breach in the Grande-Digue sand spit. The breach, which was developed in the mid-1980s, has raised concerns about its potential impacts on water renewal time and water quality in the inner bay. The aims of this study, using mathematical modeling approaches, were to evaluate the flow regimes passing through the breach and influences on the distribution of dissolved matter, providing insights into whether the breach should be allowed to naturally evolve or be artificially infilled to prevent contaminant stagnancy in the bay. The study considered three simulation scenarios to comprehend the water renewal time and the role of the breach in the environmental management of Shediac Bay. Results indicated that completely closing the breach would significantly increase the water renewal time in the inner bay, although the spatial extent of this increase is limited. However, the study identified some limitations, including the need to better define the concentration limit for considering water as renewed and the lack of consideration of dynamic factors such as wind and wave effects.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.994

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)0.0000.000

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 head0.004
GPT teacher head0.188
Teacher spread0.184 · 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 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

Citations1
Published2024
Admission routes2
Has abstractyes

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