Microcapsulated biocides for the targeted control of invasive bivalves.
Bibliographic record
Abstract
Invasive alien species (IAS) are one of the greatest drivers of ecological change. Typically, control uses chemical agents that often are ineffective, harmful to non-target organisms, and environmentally persistent. Bivalves are frequently high impact IAS, but have proven particularly hard to control due to their valve-closing response when exposed to conventional control agents. Microencapsulation of biocides with edible coatings represents a highly targeted delivery route, bypassing avoidance responses and accumulating in bivalves through their prodigious filter feeding. Uneaten microcapsules degrade and become biologically inactive within hours thus reducing potential impacts on non-target biota. We manufactured two new formulations of microcapsules (BioBullets). Particles were designed to mimic natural food particles (algae) in terms of size (9.5 ± 0.5 to 19.4 ± 1.3 SE µm diameter), buoyancy (near neutral) and shape (spherical). Laboratory exposures demonstrated that two formulations effectively controlled the Gulf wedge clam Rangia cuneata, an IAS currently spreading rapidly through Europe. A single dose of 2-6 mg L-1 of the active ingredient in a static system achieved 90% mortality after 30 days of exposure. Microencapsulation offers an effective and targeted management tool for rapid responses following the early detection of both Gulf wedge clams and many other filter-feeding IAS, and may be especially effective in closed systems or where populations remain very localised.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".