Aquatic invasive alien species : top issues for their management
Bibliographic record
Abstract
In November 2014, the European Union (Member Organization) (EU) published a new Regulation to address invasive alien species (IAS) and protect biodiversity. This Regulation entered into force across the EU in January 2015. Its aim is to “prevent the introduction of, control or eradicate alien species which threaten ecosystems, habitats or species”. In an effort to provide focus to the Regulation prior to its publishing and to identify the major issues relating to IAS in Europe (28 countries of the EU and other European countries), the views of invasive species experts from around the world were sought. These were consolidated at an international conference (Freshwater Invasives – Networking for Strategy [FINS]) that was held in Ireland in April 2013. A major outcome from this meeting of experts was the production of the “Top 20” IAS issues that relate primarily to freshwater habitats but are also directly relevant to marine and terrestrial ecosystems. This list will support policy-makers throughout the EU as preparations are made to implement this important piece of legislation. A further outcome from the conference was the formation of an expert IAS advisory group to support EIFAAC in its work on invasive species.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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".