A qualitative biological risk assessment for vase tunicate Ciona intestinalis in Canadian waters: using expert knowledge
Bibliographic record
Abstract
Abstract Therriault, T. W., and Herborg, L-M. 2008. A qualitative biological risk assessment for vase tunicate Ciona intestinalis in Canadian waters: using expert knowledge. – ICES Journal of Marine Science, 65: 781–787. Non-indigenous species (NIS) can pose a significant level of risk, through potential ecological or genetic consequences, to environments to which they are introduced. One way to characterize the overall risk posed by a NIS is to combine the probability and consequences of its establishment in a risk assessment that can be used to inform managers and policy-makers. The vase tunicate Ciona intestinalis is considered to be a cryptogenic species in eastern Canadian waters, but has not yet been reported from Pacific Canada. Because it is unclear what level of risk it poses for Canadian waters, we conducted a biological risk assessment for C. intestinalis and its potential pathogens, parasites, and fellow travellers. An expert survey was conducted to inform the risk assessment. The ecological risk posed by C. intestinalis was considered high (moderate uncertainty) on the Atlantic coast, and moderate (high uncertainty) on the Pacific coast. The genetic risk posed by C. intestinalis was considered moderate on both coasts, with low uncertainty on the Atlantic coast and high uncertainty on the Pacific coast, where hybridization with Ciona savignyi may be possible. Pathogens, parasites, and fellow travellers were considered to be a moderate ecological risk and a low genetic risk (with high uncertainty) for both coasts.
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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 | 0.045 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".