Can <i>Cylindrospermopsis raciborskii</i> invade the Baltic Sea?
Bibliographic record
Abstract
Management actions against invasive species are usually most efficient during early stages of invasion. Monitoring for early detection is therefore part of many management plans. However, if monitoring efforts do not match suitable habitat areas, detecting the initial stages of an invasion may fail. We highlight this mismatch by assessing which areas have suitable habitats for an invasion of the cyanobacterium Cylindrospermopsis raciborskii in the Baltic Sea, and compare these with the areas that are currently monitored for algal blooms. Establishment of this potential toxin-producer in the Baltic Sea could have serious socio-economic consequences for tourism and recreation, as well as fisheries and aquaculture in the coastal regions. We estimate the coastal areas of the eastern Gulf of Finland as the most suitable area for establishment because of low salinity and high summer seawater surface temperatures. The species is not yet reported in the Baltic Sea, but in the suitable-habitat areas indicated by our assessment, very little monitoring is currently being done. We suggest several lines of research and monitoring to increase the probability of early detection and better predictions for the future distribution of the 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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".