Group size influences maternal provisioning and compensatory larval growth in honeybees
Bibliographic record
Abstract
Environmental variation selects for the adaptive plasticity of maternal provisioning. Even though developing honeybees find themselves in a protected colony environment, their reproductively specialized queens actively adjust their maternal investment, even among worker-destined eggs. However, the potentially adaptive consequences of this flexible provisioning strategy and their mechanistic basis are unknown. Under natural conditions, we find that the body size of larvae hatching from small eggs in large colonies converges with that of initially larger larvae hatching from large eggs typically produced in small colonies. However, large eggs confer a persistent body size advantage when small and large eggs are cross-fostered in small and large colonies, respectively. We substantiate the increased maternal investment by identifying growth-promoting metabolomes and proteomes in large eggs compared to small eggs, which are primarily enriched in amino acid metabolism and cell maturation. Thus, our study provides a comprehensive adaptive explanation for the worker egg size plasticity of honeybees.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".