Effects of building features on density and flock distribution of feral pigeons <i>Columba livia</i> var. <i>domestica</i> in an urban environment
Bibliographic record
Abstract
We censused feral pigeons (Columba livia) living in Milan, Italy (a 181-km 2 area), between July 1999 and February 2000 by means of linear transects to examine population densities in different urban habitats and the relationships between population density and structural features of buildings. The pigeon population of Milan was 103 650 birds, with an average density of 570/km 2 . Population density increased significantly from farmland (434 birds/km 2 ) to the suburbs (604 birds/km 2 ) and from the suburbs to the centre of the city (2083 birds/km 2 ). There was a positive relationship between both bird number and flock number and the abundance of buildings constructed before 1936. There were no significant associations between either bird number or flock number and the abundance of buildings when we did not consider date of construction. This indicated active selection of old buildings by feral pigeons.
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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 | 0.000 |
| 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) | 0.000 | 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".