Intersexual social behavior of urban white-tailed deer and its evolutionary implications
Bibliographic record
Abstract
White-tailed deer ( Odocoileus virginianus (Zimmermann, 1780)) are now common in many urban environments throughout their geographic range. Yet, how male and female deer in the urban environment associate, behave socially, and the evolutionary implications of that behavior remains unstudied. We examined predictions of the predation risk and the social factor hypotheses to explain intersexual grouping patterns and social behavior observed in white-tailed deer inhabiting the small city of San Marcos (population size ~45 000) in central Texas. Two routes were surveyed weekly from a vehicle at dawn and dusk for 1 year. Group size, composition, distance to vehicle, and alarm state of deer to the vehicle were recorded. Focal animal sampling was used to measure the time males and females spent and number of aggressions within one body length of each other when in groups. Female-only groups were most prevalent year round followed by mixed-sex groups, which increased in prevalence in summer and during the mating season. Alarm state was weakly related to group size but not to group composition. Males were farther apart and more aggressive than females in groups. Proportion of males in mixed-sex groups declined with increased group size. Intersexual patterns of grouping and social behavior of urban deer supported the social factor hypothesis but not the predation risk hypothesis.
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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 | 0.001 | 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".