Competitive interactions between gray triggerfish (<i>Balistes capriscus</i>) and red snapper (<i>Lutjanus</i> <i>campechanus</i>) in laboratory and field studies in the northern Gulf of Mexico
Bibliographic record
Abstract
Field removal and laboratory studies examined competitive interactions between gray triggerfish (Balistes capriscus) and red snapper (Lutjanus campechanus). In field studies, all gray triggerfish and red snapper were counted and sizes estimated on 24 reef sites. Gray triggerfish were then removed from half of these reef sites, resulting in significantly fewer gray triggerfish on the removal reefs at the start of the experiment. After 7 months the experiment ended and reef sites were resurveyed. Gray triggerfish decreased on both treatments, while the mean number of red snapper did not differ between treatments; however, there were significantly more small (<400 mm total length) red snapper on reefs where gray triggerfish were removed. In seven laboratory growth trials (30 to 35 days each), red snapper held with gray triggerfish had significantly lower growth rates and numerous bite marks compared with red snapper alone. These competitive interactions indicate that management efforts to rebuild and increase gray triggerfish populations may have unintentional negative effects on red snapper populations, particularly for smaller fish.
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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 | 0.001 | 0.001 |
| 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".