Habitat selection by the Puerto Rican yellow-chinned anole,<i>Anolis gundlachi</i>
Bibliographic record
Abstract
Habitat selection can directly affect the fitness of an individual and the evolutionary dynamics of the population to which that organism belongs. We studied habitat use of the Puerto Rican yellow-chinned anole (Anolis gundlachi Peters, 1876) to examine whether this arboreal lizard uses its environment in a nonrandom manner. Males and females preferred woody vegetation substrates over nonwoody plants and sierra palms (Prestoea acuminata var. montana (Graham) A. Henderson and G. Galeano) as perching sites, and they also selected wider vegetation than what was randomly available. Selection for minimizing conspicuousness to potential predators and for increased locomotion capacity may help explain the preference for woody substrates and broader surfaces, respectively. Anolis gundlachi relies almost exclusively on visual cues for foraging and social interactions, and using wider perches also increases an individual's ability to scan a larger proportion of its territory. Our findings thus indicate that the nonrandom habitat use of free-ranging A. gundlachi leads to the selection of perching substrates that may increase performance of ecologically relevant capabilities.
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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 | 0.000 | 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".