Manejo integrado de podas de cultivo de arándano (Vaccinium corymbosum L)
Bibliographic record
Abstract
In Colombia the cultivation of blueberry (Vaccinium corymbosum L.), has been implemented in recent years. It is a new crop that has brought profit and profitability for producers. The blueberry is a commercially attractive in countries like Chile, United States and Canada for its medicinal properties, flavor, texture, among other attributes (Garcia, 2007) fruit. Cranberry cultivation in Colombia is from Chile, since plants are imported from that country. Because of this national suppliers pruning techniques partial disorganized, or choose to imitate pruning processes developed in other countries. A clear example are the plants that have been completely or partially pruned, in which a marked increase in the growing points, and an excessive amount of short shoots and branches with no effect (Garcia, 2007) is seen. The national picture shows clearly the lack of detailed studies for the management of pruning under local conditions. Farmers are exposed to have plants in poor condition, with problems in their formation, growth, development and fruit production. This monograph is intended from the literature review, make a first contribution to the reader and the domestic producer, providing general information on the criteria for pruning fruit trees and provide an approach to the management of pruning blueberry.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".