WOODPECKER CAVITY‐TREE SELECTION IN THE ECUADOREAN AMAZON REGION
Bibliographic record
Abstract
Abstract ∙ Tree cavities are important as sites for nesting and roosting, but their availability or use has been little studied in the Neotropics. We studied woodpecker (Picidae) cavity‐tree selection in disturbed and undisturbed landscapes in the Amazonian region. We found that woodpeckers excavated predominantly in large dead trees (mean diameter 44 cm). We highlight the importance of dead trees as substrates for cavities in the Ecuadorean Amazon region. We propose that woodpeckers in our study region are potentially important cavity formation agents for other cavity‐nesters, especially in disturbed landscapes.Resumen ∙ Selección de árboles para excavar cavidades por pájaros carpinteros en la región Amazónica Ecuatoriana Las cavidades en árboles son importantes para animales como sitios para anidar y dormir, pero su disponibilidad o uso han sido poco estudiados en el Neotrópico. Estudiamos la selección de árboles como sustratos para cavidades hechos por pájaros carpinteros (Picidae) en paisajes perturbados y no perturbados. Encontramos que los pájaros carpinteros excavaban predominantemente en árboles muertos grandes (diámetro medio de 44 cm). Destacamos la importancia de los árboles muertos como sustratos para las cavidades en la región amazónica ecuatoriana. Proponemos que los pájaros carpinteros son potencialmente importantes para la formación de cavidades para otras aves en la región de estudio.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".