Rapid adoption of nest boxes by Prothonotary Warblers (<i>Protonotaria citrea</i>) in mesic deciduous forest
Bibliographic record
Abstract
Breeding territory selection in Prothonotary Warblers (Protonotaria citrea (Boddaert, 1783)) is thought to hinge on standing water, with a strong preference for low-lying areas prone to seasonal flooding. However, we have observed this species nesting in much drier areas than previously reported. We recently initiated a study of the Carolina Wren (Thryothorus ludovicianus (Latham, 1790)) using wooden nest boxes, and nearly 60% of all nests produced in these boxes during the initial study year were produced by Prothonotary Warblers, despite this species being absent from our field site during the year preceding nest-box availability. Most nests were produced in dense, closed-canopy forest with a thick shrub layer >100 m from any water body. There was no difference in the mean distance from water between nests of the Prothonotary Warbler and those of the Carolina Wren, a habitat generalist that does not nest over water. We then observed a 60% increase in the number of Prothonotary Warbler nests the following year, along with significant increases in breeding productivity. Although they nested on sites that they are not thought to prefer, our observations suggest that Prothonotary Warblers may nest in drier areas than usual if appropriate nest cavities are provided.
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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".