Using fine-scale spatial analysis to study behavioural strategies prevalence in wild groups of drift-feeding fish
Bibliographic record
Abstract
Key aspects of the social behaviour of groups of drift-feeding fish can be inferred by the way space is shared between group members, because they inhabit a very dynamic and complex environment where spatial positions have a direct impact on fitness-related traits. Therefore, the spatial analysis of such a system can reveal important insights into behavioural ecology of fish, but so far, technical constraints limited this approach to only large salmonids. We used a digital imaging technique to monitor movements and behaviour of free-ranging groups of juvenile galaxiids (Galaxias anomalus) facing two contrasting physical and social contexts. We described the spatial structure of these groups and studied individual space use in relation to their social behaviour. We found that prevalence of territorial behaviour differs greatly between sites, which suggests that groups were displaying different social organisation. This study showed that detailed spatial analysis of space use and behaviour of drift-feeding fish could provide new insights into the social organisation of group-living animals.
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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 | 0.002 | 0.001 |
| 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".