Eurasian tench (<i>Tinca tinca</i>): the next Great Lakes invader
Bibliographic record
Abstract
A globally invasive fish, Eurasian tench (Tinca tinca) is spreading through the St. Lawrence River and poses an imminent invasion threat to the Great Lakes. Following its illegal release into a tributary of the St. Lawrence River in 1991, tench has spread throughout the river’s main stem over the past decade, and its abundance in commercial fishing bycatch in the river has grown exponentially. The tench is a generalist benthic consumer with largely undocumented ecological impacts in North America. Reports from other invaded regions indicate that it can compete with other benthic fishes, host a diverse assemblage of parasites and pathogens, degrade water clarity in shallow lakes, limit submerged macrophyte growth, reduce gastropod populations, and promote benthic algal growth through top-down effects. Risk assessments and climate-match models indicate that the Great Lakes are vulnerable to tench invasion, and they signal the need for timely comprehensive actions, including development and implementation of monitoring and rapid-response protocols, including prevention or slowing of natural dispersal through canals.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".