Reduced parasite infestation in urban Eurasian blackbirds (Turdus merula): a factor favoring urbanization?
Bibliographic record
Abstract
Humans nowadays dramatically alter environmental and ecological conditions worldwide. One of the most extreme forms of anthropogenic land-use alteration is urbanization. Animals thriving in urban areas are not only exposed to different environmental conditions compared with their nonurban conspecifics, but prevalence and impacts of wildlife diseases on urban populations may also be affected. In the present study, we tested whether blood-parasite prevalence differs between urban and forest habitats by comparing haematozoan infections of urban and forest-living Eurasian blackbirds ( Turdus merula L., 1758). In total, 76% of Eurasian blackbirds were infected with haematozoa and we detected five different blood parasite genera in both habitats. Blood-parasite prevalence varied both between years and between spring and summer in both urban and forest populations. Forest blackbirds had more parasite genera per individual than urban blackbirds, and in summer, forest blackbirds had higher blood-parasite prevalence than their urban conspecifics. These differences in blood-parasite prevalence between urban and forest blackbirds suggest a lower risk of haematozoan infections in urban than in forest habitats. The lower parasite prevalence could be one of the factors favoring the invasion of urban ecosystems.
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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".