Spring phenological adaptation of blue honeysuckle (<i>Lonicera caerulea</i> L.) foundation germplasm in a temperate climate
Bibliographic record
Abstract
Blue honeysuckle (Lonicera caerulea L.) is a novel fruit crop that stands out for its northern climatic adaptation. Understanding spring phenological adaptation to temperate climate is central to development of a broader range of production and greater mainstream crop potential. In 2012 and 2013 across three sites in the Fraser Valley, British Columbia, spring phenophases from bud break to fruit harvest were determined across three foundation groups. Genetic variability is characterized for Russian, Japanese, and Kuril blue honeysuckle foundation groups used in breeding at the University of Saskatchewan, Saskatoon, SK. Germplasm group membership is the principal feature of phenological adaptation. Although temperate climate adaptation is limited in the Russian germplasm, the intermediate Japanese and later Kuril spring phenology provide an adequate degree of temperate climate adaptation to facilitate commercial production. These findings demonstrate that blue honeysuckle has phenological adaptation to a temperate climate. Diversity between and within genetic groups presents opportunities for crop enhancement, especially through breeding for later bloom periods.
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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 | 0.000 |
| 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".