Investigation of Riverine Loading Impacts on the Lower Green Bay Hydrodynamic Regimes
Bibliographic record
Abstract
The world’s largest freshwater estuary, Green Bay, was a pristine habitat for centuries. The development of manufacturing industries in the area caused widespread pollution and natural habitat loss that resulted in the designation of the Lower Fox River and the Lower Green Bay system as an area of concern (AOC) by the International Joint Commission of Canada and the United States. The world’s largest polychlorinated biphenyls (PCB) cleanup and habitat restoration projects took place in the Lower Fox River. Lower Green Bay receives flows and sediment and nutrient loadings from five major tributaries: Fox River, Menominee River, Oconto River, Peshtigo River, and Duck Creek. Previous studies showed that most nutrient inputs to Green Bay are delivered by the Fox River—estimated to be approximately one-third of the total nutrient loading to Lake Michigan. The authors previously investigated loading impacts from the two largest tributaries to the bay, namely the Fox and Menominee Rivers, using the Finite-Volume Community Ocean Model (FVCOM), an unstructured-grid, free-surface, three-dimensional circulation model. This study investigates the impacts of the inclusion of the additional tributaries Oconto River, Peshtigo River, and Duck Creek on the Green Bay circulation and thermal regimes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".