Effects of bird feeder density on the foraging behaviors of a backyard songbird (the House Finch, <i>Haemorhous mexicanus</i>) subject to seasonal disease outbreaks
Bibliographic record
Abstract
Provisioning of wildlife, such as backyard bird feeding, can alter animal behavior and ecology in diverse ways. For species that are highly dependent on supplemental resources, it is critical to understand how variation in the degree of provisioning, as occurs naturally across backyards, alters wildlife behavior and ecology in ways potentially relevant to disease spread. We experimentally manipulated feeder density at suburban sites and tracked local abundance, foraging behaviors, body mass, and movement in House Finches (Haemorhous mexicanus (P.L. Statius Müller, 1776)), the primary host of a pathogen commonly spread at feeders. Sites with high feeder density harbored higher local House Finch abundance, and birds at these sites had longer feeding bouts and total time on feeders relative to sites with low feeder density. House Finches at high-density feeder sites had lower residual body mass despite greater apparent feeder access. Finally, birds first recorded at low-density feeder sites were more likely to move to neighboring high-density feeder sites than vice versa. Because local abundance and time spent on feeders have both been linked with disease risk in this species, the effects of heterogeneity in bird feeder density on these traits may have important consequences for disease dynamics in this system and more broadly.
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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 | 0.000 | 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".