Hydrodynamic–biogeochemical modelling of Lake Winnipeg for eutrophication management
Bibliographic record
Abstract
Harmful algae blooms occur regularly in Lake Winnipeg. We apply a two-dimensional hydrodynamic and biogeochemical model, to investigate bloom causes and develop lake management tools. The model simulated hydrodynamics with root-mean-square errors in temperature and currents <2.5 °C and <4 cm s−1, respectively. Biogeochemical parameters were reproduced to the same order as observed. Light and nitrogen (N) limited algae growth were simulated within the Red River plume and North Basin, respectively, in agreement with observations. We model low ratios of N to phosphorus (P), which favours growth of N-fixing cyanobacteria. Our model suggests that reductions in P alone will help mitigate cyanobacteria blooms and that reductions of N or both N and P may increase cyanobacteria. However, we do not model intracellular nutrient storage, which may enable N-limitation in cyanobacteria. The ability of the model to reproduce many eutrophication-related processes supports further model development for nutrient management.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".