Diet of common dolphinfish (<i>Coryphaena hippurus</i>) in the Pacific coast of Ecuador
Bibliographic record
Abstract
The diet and the feeding habits of the common dolphinfish (Coryphaena hippurus) in the Pacific coast of Ecuador was assessed by examining 320 stomachs of individuals ranging from 51 to 149 cm in total length. Fish was the predominant prey group in the diet (Alimentary Index, %AI = 95.39) followed by cephalopods (%AI = 4.13) and crustaceans (%AI = 0.48). Among the 17 prey items that make up the dolphinfish diet, the Exocoetidae family was the most important prey (%AI = 57.13),Dosidicus gigasbeing the most abundant invertebrate species (%AI = 7.65). Feeding patterns were evaluated using the graphing method of Amundsen, which suggested that this species shows a varying degree of specialization on different prey taxa. Thus, while some species were unimportant and rare (Hippocampus hippocampus, Lagocephalus lagocephalus, Gobiidae andArgonautasp.), several dolphinfishes showed a high degree of specialization on Scombridae,Pleuroncodes planipes, Portunus xantusiiandOpisthonema libertate. Size-related and temporal shifts in dietary composition were investigated by PERMANOVA analysis, which showed wide variations among size classes and periods of capture. The results of this study indicate that the common dolphinfish is an opportunistic feeder, which is capable of consuming a wide variety of schooling epipelagic organisms.
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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".