ATTRACTING BIRDS TO YOUR YARD
Bibliographic record
Abstract
Attracting Birds to Your YardBirds capture the imagination of homeowners from all walks of life.A glance out a window during fall or spring may reveal a pinstriped blackpoll warbler busily feeding during a break from migratory flights that take it to places as far away as the boreal forests of Canada or the mountain forests of South America.Lifeless and cold winter days may be enhanced by the company of a flock of chickadees.A morning on the back porch may turn into a front seat for the first attempts at flight by recently hatched robins.Backyard habitats are important resources for many birds, and homeowners can take actions to increase the attractiveness of their yard for birds.Additionally, the same practices deemed desirable by birds can increase property values, improve aesthetics, help conserve energy costs with shade or insulation from strong winds, reduce the abundance of certain insect pests, and provide an enriching experience to observe and learn about the birds in your own backyard.This publication explores those practices and offers guidance on making the most of your yard for wildlife.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.026 |
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".