Modelling of Hydrological and Non-Point Source Pollution Regimes in Big Creek Watershed
Bibliographic record
Abstract
The hydrological and non-point source loading processes of the Big Creek Marsh and Big Creek Watershed were investigated in this study. The Big Creek Watershed in south-western Ontario was modelled with AnnAGNPS (Annualized AGricultural Non-point Source). The AnnAGNPS model was first calibrated and validated with observed streamflow data in the neighbouring Canard River Watershed. Nash-Sutcliffe model efficiencies for monthly streamflow predictions were 0.75 and 0.72, for the calibration and validation periods. In the Big Creek Watershed the north-eastern and south-eastern regions were found to produce the highest sediment and nutrient loads. A water budget model for the Big Creek Marsh was developed to investigate hydrologic historic processes in the wetland. In the model assessment three potential wetland operating plans were reviewed and compared to the observed pumping data. A sensitivity analysis of the water budget model was performed. An investigation of Lake Erie's influence on the Marsh was also included.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".