Interactions between hooded crows ( <i>Сorvus cornix</i> ) and Eurasian magpies ( <i>Pica pica</i> ) and their nesting site preferences in anthropogenic landscapes
Bibliographic record
Abstract
The interrelationships of many urban birds, especially the ones that influence other birds’ nesting populations, remain understudied. Hooded crows (Corvus cornix) and Eurasian magpies (Pica pica) are numerous in cities and are aggressive species whose habitats significantly overlap. The influence of habitat on the nesting preferences of magpies and hooded crows was studied in Poltava city (central Ukraine). Spatial and statistical tests were computed in order to analyze spatial patterns and distribution of both species, as well as the influence of crows’ presence on magpies’ nesting. Magpies preferred plots in private sectors, avoiding industrial and tall building areas, whereas the density of hooded crows was higher in parks and green spaces. The height of magpies’ nests appeared to be determined by tree height, but not by anthropogenic pressure. Crows were nesting only in high trees, which had an influence on their distribution in Poltava city. Spatial analysis of habitat preference demonstrated that magpies and crows prefer habitats dominated by lawns, roads, and other artificial surfaces, and avoid dense tree cover. Magpies avoided nesting near crow nesting sites, up to a distance of 700 m. Competition between magpies was not noticed, but rather a tendency toward aggregation of their nests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".