Robots as Vectors for Marine Invasions: Best Practices for Minimizing Transmission of Invasive Species Via Observation-Class ROVs
Bibliographic record
Abstract
Remotely operated vehicles (ROVs) present a potential risk for the transmission of invasive species. This is particularly the case for small, low-cost microROVs that can be easily transported among ecosystems and, if not properly cleaned and treated, may introduce novel species into new regions. Here we present a set of 5 best-practice guidelines to reduce the risk of marine invasive species introduction for microROV operators. These guidelines include: educating ROV users about the causes and potential harm of species invasion; visually inspecting ROVs prior to and at the conclusion of each dive; rinsing ROVs in sterile freshwater following each dive; washing ROVs in a mild bleach (or other sanitizing agent) solution before moving between discrete geographic regions or ecosystems; and minimizing transport between ecosystems. We also provide a checklist that microROV users can incorporate into their pre- and post-dive maintenance routine.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".