Is Fall Burning Preferable to Spring Burning for Promoting Growth Characteristics Favorable for Mechanical Harvesting in Vaccinium myrtilloides Michaux?
Bibliographic record
Abstract
Periodic prescribed burns of lowbush blueberry barrens promote high yield, aid in weed control, and reduce fungal and insect damage. Whether such prescribed fires should be set in the autumn or the spring has been a matter of some dispute. Previous research on Vaccinium angustifolium Aiton suggested some advantages to autumnal burning, but few data have been collected on V. myrtilloides Michaux. To evaluate whether time of burning affected plant qualities most favorable for mechanical harvesting, such as stem length and lateral branching, a series of experiments was conducted on V. myrtilloides . Differences in stem length, numbers of lateral branches, and buds per stem were nonsignificant among plants burned in fall vs. those burned in spring. In three of four experiments, however, fall burns resulted in the growth of fewer lateral branches. Furthermore, among the four experiments, growth responses were more uniform following fall than following spring burns. We therefore suggest that, where possible, fall burns should be prescribed for blueberry plants that will be mechanically harvested.
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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) | 0.001 | 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".