Invasive aquatic plants in the aquarium and ornamental pond industries: a risk assessment for southern <scp>O</scp> ntario ( <scp>C</scp> anada)
Bibliographic record
Abstract
Summary An assessment of the invasive risk associated with the establishment and dispersal of plants available in the aquarium and ornamental pond industries in the Greater Toronto area (Canada) was made. In the risk model, sales volumes of individual taxa were used as a proxy for propagule pressure, to assess pathway risk potential. Organism risk potential, the ability to become established and disperse associated with a release, was assessed using an analysis of the biological traits of the species. Discriminant correspondence analysis was used to predict which biological traits were useful in discriminating native plants from alien invasive plants and alien non‐invasive plants. Importantly, a relatively small number of biological traits appear to be useful in predicting whether an alien aquatic plant had the characteristics that would support establishment and/or dispersal in new environments. Aquatic plants distributed by the industries that are cold tolerant, able to propagate by fragments and use a number of dispersal methods are of particular concern as potential invaders. The model identified 11 alien plants in the trade that have a high risk of becoming invasive, and an additional 52 with moderately high risk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".