Assessing the fast geographic range expansion of the Asian green mussel, Perna viridis (Bivalvia: Mytilidae), in the Brazilian coastal waters
Bibliographic record
Abstract
ABSTRACT Perna viridis (Linnaeus, 1758) is an invasive species that has caused major environmental and economic impacts in several regions where it has been introduced. In Brazil, since its introduction in 2019, it has been rapidly expanding its distribution. We aimed at describing its geographic distribution expansion on the southeast and southern coast of Brazil based on biodiversity monitoring surveys, underwater observations documented through photography, and using the Global Biodiversity Information Facility. The collected individuals were identified through morphological and molecular analyses, confirming the identity of the species. The available evidence suggests it is rapidly expanding its geographic distribution in Brazil. In total, we provide 53 new locality records where the species was found. This mollusk is known for its great invasive potential and can become an important environmental problem, as it can alter the structure of natural habitats and ecosystems, and negatively affect the commercial harvest of economically important native marine organisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".