Patterns of invasion in the Laurentian Great Lakes in relation to changes in vector activity
Bibliographic record
Abstract
ABSTRACT The Laurentian Great Lakes basin has been invaded by at least 182 non‐indigenous species. A new invader is discovered every 28 weeks, which is the highest rate recorded for a freshwater ecosystem. Over the past century, invasions have occurred in phases linked to changes in the dominant vectors. The number of ship‐vectored invaders recorded per decade is correlated with the intensity of vessel traffic within the basin. Ballast water release from ocean vessels is the putative vector for 65% of all invasions recorded since the opening of the St. Lawrence Seaway in 1959. As a preventive measure, ocean vessels have been required since 1993 to exchange their freshwater or estuarine ballast with highly saline ocean water prior to entering the Great Lakes. However, this procedure has not prevented ship‐vectored species introductions. Most ships visiting the Great Lakes declare ‘no ballast on board’ (NOBOB) and are exempt from the regulation, even though they carry residual water that is discharged into the Great Lakes during their activities of off‐loading inbound cargo and loading outbound cargo. Recently introduced species consist predominantly of benthic invertebrates with broad salinity tolerance. Such species are most likely to survive in a ballast tank following ballast water exchange, as well as transport in the residual water and tank sediments of NOBOB ships. Thus, the Great Lakes remain at risk of being invaded by dozens of euryhaline invertebrates that have spread into Eurasian ports from whence originates the bulk of foreign ships visiting the basin.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".