Group Adherence in Endangered California Least Terns (Sternula antillarum browni)
Bibliographic record
Abstract
Colonial nesting in seabirds is advantageous for protection from predators—spotting a predator, mobbing, and predator swamping. Familiarity with nesting areas gives knowledge of protected sites and may promote site fidelity. Familiarity with nearest neighbors helps nesting success by lessening intraspecific aggression and increasing social facilitation, and may promote group adherence. Group adherence has been proposed as more important than site tenacity for some species where nesting areas are frequently disturbed. Ground-nesting terns often nest at disturbed sites, and their colonies are accessible to predators. Serendipitously, I was able to test the concept of group adherence in individually color-marked California Least Terns Sternula antillarum browni during early egg-laying when some nests in a colony in southern California were depredated, and the adults deserted. A week later, I found the majority of those birds nesting at the edge of a small Least Tern colony 28 km distant, where they laid a second clutch and remained at the site the rest of the breeding season. The following breeding season, no color-marked terns nested again at the small colony where they had moved after disturbance.
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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".