The Present Distribution and Predicted Geographic Expansion of the Floodwater Mosquito<i>Aedes sticticus</i>in Sweden
Bibliographic record
Abstract
The mass emergence of floodwater mosquitoes, in particular Aedes sticticus and Aedes vexans, causes substantial nuisance and reduces life quality for inhabitants of infested areas and can have a negative impact on the socio-economic conditions of a region. We compared the previous, present, and predicted geographic distribution of Ae. sticticus in Sweden. Previous records from the literature until 1990 list the species in three out of 21 Swedish counties. Beginning in 1998, studies show that the present distribution of the species covers 11 counties, with highest abundances in an east-west belt in Central Sweden. Using climate data from the present and predicted climate scenarios, the expected distribution of Ae. sticticus in 2020, 2050, and 2080 could be modelled using GIS. As variables, mean temperatures and cumulative precipitation between May and August and degree slope were chosen. The predicted geographic distribution of Ae. sticticus will continue to increase and include 20 out of 21 Swedish counties. The expected temperature rise will increase the suitable area towards the northern part of Sweden by 2050. Some non-suitable areas can be found along the south-east coast due to insufficient amount of precipitation in 2050 and 2080. Modelling the expected distribution of a species using predicted climate change scenarios provides a valuable tool for risk assessments and early-warning systems that is easily applied to different species and scenarios.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".