Data for Chretien et al. 2021 Group size influences individual metabolic traits in a social fish
Bibliographic record
Abstract
Group living is widespread among animal species and yields both costs and benefits. Presence of conspecifics can restrict or enhance the expression of individual behaviour, and the recent social environment is thought to affect behavioural responses in later contexts, even when individuals are alone. However, little is known about how social dynamics influence the expression of individual physiological traits, including metabolic rates. There is some evidence that shoaling can reduce fish metabolic rates, but habitat conditions such as shelter availability may generate density-dependent influences on individual metabolic rates. We investigated how social group size and availability of shelter influence Eurasian minnow Phoxinus phoxinus metabolic rates estimated by respirometry in the presence or absence of plant shelter. Respirometry trials were conducted before and after we housed fish for three weeks in a social treatment consisting in a specific group size (n= 4 or 8) and shelter availability (presence or absence of plant shelter in the holding tank). Minimum day-time and night-time metabolic rates estimated while in presence of plant shelter were lower than when estimated in absence of plant shelter, both before and after individuals were housed in their social group size and shelter availability treatment. Standard metabolic rate was higher for fish held in groups of four as compared to fish held in groups of eight while maximum metabolic rate showed no difference. Shelter availability during the social treatments did not influence standard or maximum metabolic rates. Our results suggest that group size may directly influence energy demands of individuals, highlighting the importance of understanding the role of social dynamics on variations in physiological traits associated with energy expenditure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.054 | 0.011 |
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".