Habitat Selection, Nest Box Usage, and Reproductive Success of Secondary Cavity Nesting Birds in a Semirural Setting
Bibliographic record
Abstract
As urban areas continue to grow and erode rural landscapes, it is critical to characterize essential habitats for all wildlife in order to set aside protected areas in an attempt to maintain diversity. We constructed and monitored 30 nest boxes for usage by secondary cavity-nesting birds each year from 2014-2016 at the John Nichols Scout Ranch located in southeast Canadian County, Oklahoma. At each of six sites, five nest boxes were situated along a transect at 15m intervals with a central box located at an abrupt edge between a wooded habitat and a grassland habitat. We measured 77 habitat variables around each nest box at 2 sampling scales, 1m2 and 10m2. We used these habitat variables and sites in which nesting occurred in a principal components analysis. Eastern Bluebirds and Carolina Chickadees nested in grassland habitats with little to no overhead canopy cover. Carolina Wrens nested in woodland areas with high amounts of litter ground cover and overhead canopy cover. Results at both spatial scales were similar. We used the simplified Morisita index to calculate niche overlap at both spatial scales. Overlap varied substantially depending on sampling scale.
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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".