Management Strategies for the Cultivation of Hop, a Specialty Crop for North Dakota
Bibliographic record
Abstract
Field experiments were conducted in 2017 and 2018 at the NDSU Horticulture Research Farm near Absaraka, ND to evaluate the growth and yield characteristics of twelve commercial hop cultivars in response to varied training densities. Cultivars were trained at two, four, and eight bines per crown each season. Cultivars produced significantly higher yield (kg/ha) trained with eight bines per crown in 2018. ?Nugget?, and ?Canadian Red Vine? significantly yielded highest in 2017. ?Nugget?, ?Canadian Red Vine?, and ?Cascade? significantly yielded highest in 2018. Research investigating mulching as a weed control method on mature hop production systems was conducted. Hop cultivars ?Cascade?, ?Santiam?, and ?Mt. Hood? were grown under landscape fabric, straw much, woodchip mulch, and a non-mulched control in a standard hop trellis system. ?Cascade? had significantly higher yield, cone size, and biomass compared to cultivars ?Santiam? and ?Mt. Hood?. No significant differences found between mulch treatment selection.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".