Alien Invasive Species Impacts on Large Lake Ecosystems and Their Economic Value
Bibliographic record
Abstract
Globalization of trade and travel has made possible the spread of alien species across the planet. Invasive species are presently considered as one of the major threats to biodiversity in many locations throughout the world. Thousands of AIS have been transported globally by a number of anthropogenically-mediated vectors, including ship-mediated vectors (e.g., ballast water, hull-fouling), recreational boating, live bait, aquarium trade, live food fish, and unauthorized introductions. Ballast water is one of the leading vectors for transporting and introducing species, both in Canada and around the world, and is responsible for the transport of at least one third of all documented marine invasions. Since invasive species have no regard for political boundaries, efforts to prevent invasions need to be interjurisdictional. Given, also that invasive species often travel as contaminants of trade transfers, for example, in the ballast tanks of ships, reducing the spread of invasive species via this pathway would either require constraints on where ships travel, or the installation onto all ships of expensive ballast treatment technology, thereby increasing the cost of shipped goods. As such cost benefit analysis involves trade-offs with other activities, complicating decisions about how impacts can best be managed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".