Native pollinators alone provide full pollination on small-scale commercial cranberry (Ericaceae) farms
Bibliographic record
Abstract
Abstract Cranberry (Vaccinium macrocarponAiton (Ericaceae)) requires insect pollen vectors to maximise fruit yield. In many areas, commercial producers use managed bees (Hymenoptera: Apidae) to supplement native pollinators. On the island of Newfoundland, Newfoundland and Labrador, Canada, due to the small number of available honey bee hives and import restrictions on commercially reared bumble bees, the use of supplemental pollinators is rare. Four farms were studied for two years to identify key pollinators and determine the relationship between fruit yield and bee abundance. The most commonly collected bees were species ofBombusLatreille (Hymenoptera: Apidae), which buzz-pollinate and are likely the primary pollinator on these farms; thus, fruit yield was examined with respect to totalBombusabundance. Stigma loading was also used as a measure of pollinator effectiveness. Contrary to expectation, there was no relationship betweenBombusabundance or stigma loading and either fruit set or weight, but there was significant year-to-year variation. Other factors were likely more important in determining yield, and further research is needed to identify those. Under current conditions, native bees provide ample pollination services for maximal yield.
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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 | 0.001 | 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 | 0.000 |
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".