Defining Best Practices for Biofouling Management as a Way to Increase Biosecurity
Bibliographic record
Abstract
Marine invasive species are a major threat to the environments they are introduced to.With the rise in international shipping, it has been found the number of invasive species established around the world has increased drastically.Ships have two main vectors that transport these species: ballast water and biofouling.Ballast water is internationally regulated and biofouling regulations are the next step in combatting the invasive species problem.There are guidelines provided by the International Maritime Organization for biofouling management and new mandatory laws for management in California and New Zealand as of this year, 2018.These regulations have provided opportunities that help policy makers understand the importance of certain best practices including the use of biofouling management plans with accompanying record books, the use of anti-fouling coatings, and the role of routine hull cleaning.Each practice comes with its own challenges that must be overcome by the development of technologies and resources that benefit the environment rather than further causing unintentional harm.The case study of international ballast water regulations gives an indication of how the world is reacting to the marine invasive species problem and shows the likely next steps for biofouling regulations spreading to an international level.Through interaction between the California State Lands Commission, the New Zealand Ministry for Primary Industries, and Hawaiian, Canadian, and Australian environmental agencies, promulgation for biofouling management has a likely future as multilateral policy across the Pacific states.This, in turn can easily spread to become international law through the International Maritime Organization Marine Environment Protection Committee.
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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 | 0.033 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.026 | 0.015 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".