Estimating pollination success with novel artificial flowers: Effects of nectar concentration
Bibliographic record
Abstract
We developed novel artificial flowers that dispense and receive powdered food dyes as pollen analogues while their nectar is replenished by capillary action. Dye receipt, which can be measured colourimetrically, is a direct surrogate for pollen receipt or female reproductive success, but can also serve to compare pollen donation (male reproductive success) from flowers with different colours of dye. By allowing captive bumble bee colonies to visit large arrays of such flowers, we investigated whether total dye receipt depended on the sugar concentration of a flower’s nectar. Estimating pollen transfer, rather than simply visitation rate, is appropriate for this question because flowers with more concentrated nectar might accrue more pollen not only through higher visitation rates but also through longer visits that transfer more pollen per visit. Flowers with richer nectar did receive more dye regardless of their spatial arrangement, but the effect was greatest when rich and poor flowers were segregated in large blocks, as opposed to being intermingled.
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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".