Pollen collection by bumblebees (<i>Bombus impatiens):</i> the effects of resource manipulation, foraging experience and colony size
Bibliographic record
Abstract
SummaryTo examine factors influencing pollen collection by bumblebees (Bombus impatiens), we compared pollen collection in free-foraging resource-manipulated colonies (i.e., pollen-and nectar-deprived vs. pollen-deprived only). Additional manipulations included prior foraging experience in Experiment 1 and colony size in Experiment 2. In Experiment 1, colonies were either deprived of both resources or deprived of only pollen and were subsequently tested while deprived of both resources. Colonies that had experience in managing both foraging tasks subsequently collected more pollen and allocated greater foraging effort than did colonies that had experience only in collecting pollen. In Experiment 2, larger colonies collected more pollen although smaller colonies collected more pollen relative to their colony size. Results show that colonies collect more pollen when deprived of both resources, exhibit foraging efficiency depending on previous tasks, and allocate foraging effort according to nutritional and energetic demands. Because pollen collection is partly regulated by nectar availability, one practical implication for growers of bumblebee-pollinated crops is that pollination may be improved by causing colonies to forage for nectar as well as pollen.
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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 | 0.000 |
| 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".