Is repeatability of metabolic rate influenced by social separation? A test with a teleost fish
Bibliographic record
Abstract
Metabolic rates are typically thought to have important influences on fitness and more broadly be relevant to the ecology and evolution of animals. Previous studies demonstrate that metabolic rates are repeatable to a certain extent under constant conditions, but how social conditions influence the repeatability of metabolic rate remains largely unknown. In this study, we investigated the repeatability of resting metabolic rate (RMR) in the highly social crucian carp ( Carassius auratus ) after being socially separated for different time periods relative to control fish that were not socially separated. We found that RMR was repeatable in fish in the control group, while the repeatability of RMR disappeared quickly (even within 7 days) when fish were exposed to social separation. This study is the first to our knowledge to examine the role of social separation for different time periods on the repeatability of intra-individual physiological variation in fish. We highlight that the inter-individual repeatability of metabolic rate can be substantial over time but was eliminated by social separation. The findings indicate that the repeatability of metabolic rate in fish is condition dependent, and that the change in repeatability of metabolic rate should not be overlooked when considering the ecological and evolutionary effects of environmental change.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".