Ergonomic skew and reproductive queuing based on social and seasonal variation in foraging activity of eastern carpenter bees (<i>Xylocopa</i> <i>virginica</i>)
Bibliographic record
Abstract
Reproductive division of labour in social carpenter bees differs from that in classically eusocial insects because reproductive output and ergonomic inputs are positively correlated—dominant females monopolize both foraging and reproduction. We quantified ergonomic skew in the facultatively social bee Xylocopa virginica (L., 1771) (eastern carpenter bee) based on detailed observations of foraging activity by individually marked females in 2009. Unusually for a univoltine bee, this species exhibits a spring foraging phase during which females feed pollen to other adults, probably as part of behavioural interactions to establish dominance hierarchies. During brood-provisioning, foraging in social nests was dominated by one female at a time, with replacement by a succession of foragers as dominants disappeared and were succeeded by a subordinate. The principal foragers (individuals that did the largest share of foraging in each colony) did 85%–100% of all pollen trips, so contributions to pollen-provisioning by female nest mates were highly uneven. Individual foraging rate was unaffected by group size and total colony foraging effort was a function of the number of foragers per group. Transient females that moved to new nests were as successful in achieving dominant forager status as females resident in their natal nests. This evidence indicates that colony social organisation is based on reproductive queues, whereby the first-ranked bee is the dominant forager and subordinates queue for opportunities to replace her.
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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 | 0.000 |
| 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".