Personality and metabolic scope in wild mice
Bibliographic record
Abstract
It is intuitive to expect a relationship between animal personality (i.e. consistent individual behavioural differences) and metabolic rate, but the literature contains mixed results. Most studies have measured resting metabolic rate (RMR); yet, other metrics such as V̇O2,max and metabolic scope may also relate to personality. Here, we explored the relationships between personality (docility and exploration) and three metabolic traits (RMR, V̇O2,max and metabolic scope) in wild mice (Peromyscus leucopus). We found no among-individual correlation (rind) between personality and motivation to run during V̇O2,max trials, suggesting that using our standard forced-exercise test did not introduce a personality-related sampling bias. At the within-individual level, we found a positive and significant relationship between docility and metabolic scope, and the correlation was entirely driven by V̇O2,max. Finally, we found a positive and significant rind between RMR and time spent grooming during the open-field test, which may be caused by the stress response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".