Fruit production in cranberry (Ericaceae: <i>Vaccinium macrocarpon</i>): a bet‐hedging strategy to optimize reproductive effort
Bibliographic record
Abstract
In the cultivated cranberry (Vaccinium macrocarpon), reproductive stems produce 1-3 fruit even though they usually have 5-7 flowers in the spring. We undertook experiments to test the hypothesis that this was an adaptive life history strategy associated with reproductive effort rather than simply the result of insufficient pollination. We compared fruit production on naturally pollinated plants with those that were either manually pollinated or that were caged to exclude insects. Clearly, insects are necessary for the effective pollination of cranberry plants, but hand pollination of all flowers did not result in an increase in fruit number. Most of the upper flowers, which had significantly fewer ovules than did the lower flowers, aborted naturally soon after pollination. However, when the lower flower buds were removed, the upper flowers produced fruit. This suggests that the upper flowers may serve as a backup if the earlier blooming lower ones are lost early in the season. Furthermore, the late-blooming flowers may still contribute to the plant's reproductive success as visiting pollinators remove the pollen, which could serve to sire fruit on other plants. These results are discussed in the context of their possible evolutionary and proximate causes.
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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) | 0.000 | 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 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".