Poster Session PESTICIDES IN AN ESTUARY ON PRINCE EDWARD ISLAND, CANADA
Bibliographic record
Abstract
Prince Edward Island (PEI) has a history of fish kills that have been linked to the use of pesti-cides. In particular, pesticides, such as azinphos-methyl and chlorothalonil, have been linked to fish kills in recent years. Azinphos-methyl, also sold under the name of Guthion, is an insecticide used to control leaf-feeding insects, such as the potato beetle and the corn borer (Kamrin 1997). Chlorothalonil is a widely used fungicide that is used to control fungal diseases, such as late blight and downy mildew (Environment Canada 2004). In many cases, pesticide-laden runoff can be implicated in fish kills shortly after a pesticide application that is followed by a rainfall event. It is noteworthy to mention that while “fish kills ” may be the most obvious consequence of such pesticide problems, pesticides kill far more than fish, and the effects of contamination on an ecosystem as a whole should be considered. However, pesticide use is a mainstay of the agriculture industry and as such has become vital to the province of PEI as a whole. Potatoes alone are the largest agricultural commodity in the province, and typically have an annual farm value nearing 200 million dollars, representing over fifty percent of total farm cash receipts (PEI Department of Agriculture, Fisheries, Aquaculture and Forestry 2004). Overall, primary agriculture and related agri-food processing contributes eleven percent to the provin-cial Gross Domestic Product (PEI Department of Agriculture, Fisheries, Aquaculture and Forestry 2004).
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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 | 0.010 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.088 | 0.006 |
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".