Temporal trends of risk of water contamination by phosphorus from agricultural land in the Great Lakes Watersheds of Canada
Bibliographic record
Abstract
van Bochove, E., Denault, J.-T., Leclerc, M.-L., Thériault, G., Dechmi, F., Allaire, S. E., Rousseau, A. N. and Drury, C. F. 2011. Temporal trends of risk of water contamination by phosphorus from agricultural land in the Great Lakes Watersheds of Canada. Can. J. Soil Sci. 91: 443-453. The indicator of risk of water contamination by phosphorus (IROWC_P) was designed to estimate the level of risk of P contamination in water and how the level of risk has changed over 25 yr (1981-2006) in agricultural watersheds of Canada. IROWC_P allows for a qualitative assessment of this risk in comparison with other regions of eastern and western Canada, and the identification of high to very high risk watersheds may require on-site assessment and the development of remedial action plans. This study presents an in-depth analysis of IROWC_P results in the major Great Lakes watersheds of Canada. The risk of water contamination by P remains acceptable (very low to moderate) in most Great Lakes watersheds, but better management practices (e.g., reduced fertilization and manure application rates) and improved control of surface runoff may be required in watersheds which are at increased risk. The Canadian watersheds of the Great Lakes basin showed a 39% reduction in their P applications in excess of crop requirements between 1981 and 2006 bringing the Ontario provincial P balance close to equilibrium in 2006. Vulnerable areas were found south of Kitchener in the Lower Grand River watershed and east of Lake Simcoe.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".