PREVENTING THE INTRODUCTION AND THE SPREAD OF FRESHWATER INVASIVE INVERTEBRATES IN ONTARIO: ASSESSMENT OF THE PROPOSED INVASIVE SPECIES ACT (BILL 37)
Bibliographic record
Abstract
Freshwater invasive species, especially invertebrates are an important environmental stressor associated with significant ecological and economic impacts particularly in the Great Lakes, one of the freshwater ecosystems with a significant number of invasive invertebrates compared to other taxa. Because of the importance that policy development and implantation play in managing invasive species for their effective prevention and spread, a policy analysis of the proposed Ontario’s Bill 37 (“An Act respecting Invasive Species”) was conducted based on an extensive literature review, the interview responses with provincial government officials, and the results from the constructed non-native species checklist. A total of 46 species were identified as having a high impact on the environment, according to the literature, among 409 species identified as recorded as non-native anywhere including native species to North America. Research attention seems to have been concentrated on high impact species despite they only represent 11.2% of the total species as well as on their main associated pathways, such as the ballast water and sediment of transoceanic and domestic ships in the Great Lakes. Particularly, research efforts are concentrated on only 16 invasive species, which are already established in the Great Lakes. Almost half of the high-impact species identified have not yet been introduced into Ontario’s freshwater ecosystems, representing a potential threat. Therefore, the implementation of Ontario’s Bill 37 is crucial for the effective prevention of the introduction and spread of invasive species in Ontario, particularly for aquatic invertebrates, however there are issues that need to be addressed before the implementation of the proposed legislation.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".