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Record W6947981163 · doi:10.4224/40002703

Preparation of a hydrodynamic model of St. Clair River with Telemac-2D, to study the impacts of potential changes to the waterways

2009· report· en· W6947981163 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2009
Typereport
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsHydraulicsNumerical modelsRepresentation (politics)BathymetryHydrology (agriculture)Mathematical modelJoint (building)

Abstract

fetched live from OpenAlex

The Hydraulics Working Group of the International Upper Great Lakes Study is investigating apparent changes which may have occurred in the St Clair River in the last few decades. For this purpose, several numerical models have been prepared in order to help in understanding the impacts of these changes by simulating various scenarios where the bathymetry of the River, its morphology, its bed material content or its bottom friction would be modified. Numerical models are developed using different assumptions so that they can best represent certain aspects of the physical problem. Therefore they vary in the representation of the physical description of the River, the representation of the hydrodynamics of the River, or in the numerical methods used to solve the fluid hydrodynamics. Each model is different and will give different solutions to the same problem. It is therefore important to compare the results from several models to be able to appreciate the variability in the solutions. The International Joint Commission retained the services of the Canadian Hydraulics Centre (CHC) of the National Research Council, to prepare one of these numerical models, so that its results can be compared with similar models. CHC chose Telemac-2D, a commercially available two-dimensional model. This report describes the preparation of this model with its calibration, and it presents the results of various scenarios which have been simulated looking at changes on the St Clair River. Since this project involved many simulations, the run numbers are identified for future reference.

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: Methods · Consensus signal: none
Teacher disagreement score0.844
Threshold uncertainty score0.311

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.028
GPT teacher head0.288
Teacher spread0.260 · 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
GenreMethods

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
Published2009
Admission routes2
Has abstractyes

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