When fish shoals meet: outcomes for evolution and fisheries
Bibliographic record
Abstract
Abstract The mechanisms underlying the social structure of free‐ranging fish shoals have received little attention in comparison to functional studies on shoaling. Recently, however, a number of investigations, both in the marine and in the freshwater environment, have begun to address the underlying mechanisms by concentrating on interactions between free‐ranging shoals. The rates of shoal encounters can influence the opportunities for individual assortment by phenotype and selection of shoal size; act as a constraint on the observed patterns of shoal structure by restricting individual choice behaviour and were found to be high in several small freshwater species (where intershoal distances were small), but lower in marine species where shoals were more dispersed. The duration of encounters may play a role in that it affects both the time available for assessment (of the encountered shoal) as well as that for exchange of individuals. Scarce published information on the outcome of shoal encounters suggests that the outcome of shoal encounters is influenced by shoal composition but not by shoal size. Individual behaviour may have evolved to maintain shoal size when shoals encounter, but when fish populations are depleted by fishing, this trait can exacerbate range and stock collapse. Furthermore, an understanding of the dynamics of shoal encounters has important consequences for the evolution of reciprocal altruism and the transmission of information through social learning within populations. Finally, information on encounter rates between shoals and the number of individuals that are exchanged on such occasions could be important for making predictions about the spread of disease through fish populations.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".