Domestic ships as a potential pathway of nonindigenous species from the Saint Lawrence River to the Great Lakes
Bibliographic record
Abstract
Abstract Ballast water moved by transoceanic vessels has been recognized globally as a predominant vector for the introduction of aquatic nonindigenous species (NIS). In contrast, domestic ships operating within confined geographic areas have been viewed as low risk for invasions, and are exempt from regulation in consequence. We examined if the St. Lawrence River could serve as a source of NIS for the Laurentian Great Lakes by surveying ballast water carried by domestic vessels and comparing biological composition in predominant St. Lawrence River—Great Lakes port-pairs in order to determine the likelihood that NIS could be transported to, and survive in, the Great Lakes. Thirteen potential invaders were sampled from ballast water, while 26 taxa sampled from St. Lawrence River ports are not reported from the Great Lakes. The majority of NIS recorded in samples are marine species with low potential for survival in the Great Lakes, however two euryhaline species (copepodOithona similis, and amphipodGammarus palustris) and two taxa reported from brackish waters (copepodMicrosetella norvegicaand decapodCancer irroratus) may pose a risk for invasion. In addition, four marine NIS were collected in freshwater samples indicating that at least a subset of marine species have potential as new invaders to the Great Lakes. Based on results from this study, the ports of Montreal, Sorel, Tracy and Trois Rivières appear to pose the highest risk for new ballast-mediated NIS from the St. Lawrence River to the Great Lakes.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".