Growing with kin does not bring benefits to tadpoles in a genetically impoverished amphibian population
Bibliographic record
Abstract
The effect of intraspecific competition can be modified through the interaction with genetic relatedness among the competing individuals. Theory of kin selection predicts that organisms should modify their behaviour to increase the fitness of their relatives and consequently their inclusive fitness. However, in populations with low genetic variation, the recognition of kin and nonkin individuals could be compromised. In this study, we tested the influence of density and relatedness on larval development in a genetically impoverished population of the pool frog ( Rana lessonae Camerano, 1882), exposing individuals from four families to two densities and to competition by full-sibling and nonkin larvae. Larvae in high-density treatment were smaller than those in low-density treatment. No effect of kin, or interaction between density and kin, was detected. However, significant differences were detected in body size among the families and high heritability for size was found in both densities. Lack of variation in recognition alleles may explain the lack of kin effects on growth, whereas variation has been maintained in life-history traits either owing to their polygenic inheritance or owing to maternal effects.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".