Berry unexpected: Nocturnal pollination of lowbush blueberry
Bibliographic record
Abstract
Cutler, C. G., Reeh, K. W., Sproule, J. M. and Ramanaidu, K. 2012. Berry unexpected: Nocturnal pollination of lowbush blueberry. Can. J. Plant Sci. 92: 707–711. Lowbush blueberry, Vaccinium angustifolium, is an economically important crop of eastern North America that is critically dependent on insect-mediated cross-pollination for successful fruit set and high yields. It is generally assumed that bees are responsible for the vast majority of lowbush blueberry pollination, and producers usually augment the natural pollination force with managed bees. Little is known, however, of the potential role of nocturnal pollinators in lowbush blueberry production. We conducted a field experiment where patches of blooming blueberry were exposed to flying insects 24 h a day, only during the day (sunrise to sunset), only at night (sunset to sunrise), or 0 h a day. We found that significant fruit set occurred on blueberry stems that were exposed only at night, although it was higher on stems exposed during the day or 24 h a day. However, ripe fruit produced on stems exposed only at night weighed just as much as those exposed 24 h. Captures with Malaise traps activated only at night consisted mainly of several families of Lepidoptera and Diptera, although we do not know if these taxa pollinated blueberries. We conclude that nocturnal pollination may contribute significantly to lowbush blueberry fruit set.
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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 | 0.000 | 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) | 0.002 | 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".