Assessing fish consumption Beneficial Use Impairment (BUI) at Great Lakes Areas of Concern: Toronto case study
Bibliographic record
Abstract
Beneficial use of fish consumption was designated impaired in the 1980s in many Areas of Concern across the North American Great Lakes. Remedial Action Plans have guided the restoration of beneficial use impairments with the goal of delisting the Areas of Concern. Here we present generic re-designation criteria and a three-tier Assessment Framework to assess the status of the fish consumption beneficial use impairments using the Toronto and Region Area of Concern as a case study. Tier 1 assessment identified that consumption advisories for many resident fish on the Toronto waterfront are non-restrictive (8+ meals month<sup>−1</sup>). Advisory assessments in Tier 1 found that most migratory fish species, Carp and White Sucker are still restrictive in some cases preventing a ‘not impaired’ re-designation. Tier 2 Comparison with Reference Sites found that the advisories for most local fish are either non-restrictive or similar to reference locations in Lake Ontario, but some advisories due to elevated levels of polychlorinated biphenyl are still more restrictive for the Toronto waterfront and do not favour a ‘not impaired’ re-designation. An evaluation of multiple lines of evidence in Tier 3 including fish contaminant trend analyses, time to reach target fish levels, sediment concentrations and fish consumption patterns resulted in outcomes ranging from <i>neutral</i> (not conclusive) to <i>not impaired</i>. As a precautionary approach, the impaired status of the beneficial use impairment should be maintained to ensure continued polychlorinated biphenyl declines in fish. It is recommended that the Remedial Action Plan team update the fish consumption survey, investigate where additional feasible actions can be taken including examining potential polychlorinated biphenyl sources on the Humber and Don Rivers, and collect new data to undertake a future assessment.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.608 | 0.002 |
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; both teacher heads agree on what is shown here.
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".