Data from: Early-life behavior, survival and maternal personality in a wild marsupial
Bibliographic record
Abstract
Individual behavior varies for many reasons, but how early in life is such variability apparent, and is it under selection? We investigated variation in early-life behavior in a wild eastern grey kangaroo (Macropus giganteus) population, and quantified associations of this behavior with early survival. Behavior of young was measured while still in the pouch and also as subadults, and we also monitored survival to weaning. We found consistent variation between offspring of different mothers in levels of activity at the pouch stage, in flight initiation distance as subadults, and in subadult survival, indicating similarity between siblings. There was no evidence of covariance between the measures of behavior at the pouch young vs subadult stages, nor of the early-life behavioral traits with subadult survival. However, there was a strong covariance between offspring and mothers’ flight initiation distance (FID) tested at different times. Further, of the total repeatability of subadult FID (55.3%), more than two-thirds could be attributed to differences between offspring of different mothers. Our results indicate that (i) behavioral variation is apparent at a very early stage of development (still in the pouch in the case of this marsupial); (ii) between-mother differences can make up much of the repeatability of juvenile behavior (or ‘personality’); and (iii) mothers and offspring exhibit similar behavioral responses to stimuli, potentially indicating heritability of behavioral responses. However, (iv) we found no evidence of selection via covariance between early-life or maternal behavioral traits and juvenile survival in this wild marsupial. Keywords: animal personality, maternal variance, early-life behaviour and survival, macropods, multivariate Bayesian statistics.
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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 | 0.001 | 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) | 0.003 | 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".