Individual prey choices of octopuses: Are they generalist or specialist?
Bibliographic record
Abstract
Abstract Prey choice is often evaluated at the species or population level. Here, we analyzed the diet of octopuses of different populations with the aim to assess the importance of individual feeding habits as a factor affecting prey choice. Two methods were used, an assessment of the extent to which an individual octopus made choices of species representative of those population (PSi and IS) and 25% cutoff values for number of choices and percentage intake of individual on their prey. In one population of Octopus cf vulgaris in Bermuda individuals were generalist by IS=0.77, but most chose many prey of the same species, and were specialists on it by >75% intake. Another population had a wider prey selection, still generalist with PSi=0.66, but two individuals specialized by choices. In Bonaire, there was a wide range of prey species chosen, and the population was specialists by IS= 0.42. Individual choices revealed seven specialists and four generalists. A population of Octopus cyanea in Hawaii all had similar choices of crustaceans, so the population was generalist by IS with 0.74. But by individual choices, three were considered a specialist. A population of Enteroctopus dofleini from Puget Sound had a wide range of preferences, in which seven were also specialists, IS=0.53. By individual choices, thirteen were also specialists. Given the octopus specialty of learning during foraging, we hypothesize that both localized prey availability and individual personality differences could influence the exploration for prey and this translates into different prey choices across individuals and populations showed in this study.
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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 | 0.001 | 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".