Data from: Wild foundress queen bumble bees make numerous, short foraging trips and exhibit frequent nest failure: Insights from trap-nesting and RFID tracking
Bibliographic record
Abstract
The overwhelming majority of research on wild bumble bees has focused on the social colony stage. Nest-founding queens in the early season are difficult to study because incipient nests are challenging to find in the wild, and the foundress queen's flight period is very short relative to the entire nesting period. As a result, natural history information on foundress queens is exceedingly rare. New methodological approaches are needed to adequately study this elusive life stage. We trap-nested wild queen bumble bees in artificial nest boxes in Gothic, Colorado, and used a custom-built radio frequency identification (RFID) system to continuously record queen foraging activity (inferred from entering and exiting the nest) for the majority of their spring flight periods. Foundress queens made frequent, short foraging trips, which tended to increase in duration over the course of the flight period. All queens who produced adult workers ceased foraging within approximately one week after workers emerged in the nest. We observed frequent nest failure among foundress queens: fewer than one quarter of queens who laid eggs in nest boxes went on to produce reproductive gynes at the end of the season. We also report nest characteristics and curious phenomena we observed, including conspecific nest invasion and queens remaining outside the nest overnight. We present this trap-nesting and subsequent RFID tracking method as a valuable, albeit resource-intensive, path forward for uncovering new information about the elusive, incipient life stage of wild bumble bees.
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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 | 0.001 |
| 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 | 0.002 |
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".