Preparation of a hydrodynamic model of St. Clair River with Telemac-2D, to study the impacts of potential changes to the waterways
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".