Use of dairies by postreproductive flocks of European starlings
Bibliographic record
Abstract
Knowledge of the behavior and movement patterns of European starlings (Sturnus vulgaris L.) is important to wildlife managers that seek to resolve conflicts at livestock facilities. We captured and radio tagged 10 starlings at each of 5 dairies in northeastern Ohio. From September 19 to October 31, 2007, we obtained sufficient data from 40 birds to study their behavior and movements. The birds visited the dairies where they were initially captured (home sites) on 85% of the days, spending 58% of each day at the dairies. Onsite arrival and departure times were 2.5h after sunrise and 3.1h before sunset. Daily visits by radio-tagged cohorts from the other dairies were greatest for the 2 most proximate dairies (1.3 km apart), with number of visits between this pairing >7× that of the 9 other pairings combined (4.1-6.5 km apart). Two birds used their home sites intermittently as roosts, arriving 3.8h before sunset and departing 0.2h after sunrise. In addition to using home-site roosts, these birds also used a distant roost (22km) that was used by 36 of the 40 birds. The efficacy of starling management programs, especially lethal management, depends on degree of site fidelity, use of other facilities, and roosting behavior. For example, starlings that use dairies as roosting sites may require a different management strategy than required at dairies used as daytime sites because of differences in arrival and departure behavior. Our research will help resource managers evaluate current management strategies already in place and change them, if needed, to fit the behavior profile of starlings using dairies and other types of livestock facilities.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".