A Journal of Botanical Garden Science
Bibliographic record
Abstract
a progress report Figlar (Figlar, 2005) recently published a comprehensive review of Asiatic evergreen magnolias, which outlined the recent advances in our understanding of these ancient and ornamental plants. He is a world authority on the taxonomy of the Magnoliaceae and past president of the Magnolia Society International. He proposed that I write an account of progress on the introduction and growth of some of the many ever-green magnolias that have arrived at the UBC Botanical Garden from China and northern Vietnam (Figure 1) in the last two decades. I hope that this paper will allow a more informed comparison between the behavior of plants growing at UBC with those growing under the more rigorous conditions of eastern North America and western Europe. The UBC Botanical Garden is located on Point Grey at the western tip of the city of Vancouver, atop 100m cliffs that overlook the Strait of Georgia. The relatively benign microclimate of the garden is due in part to this body of water, which separates the BC mainland from Vancou-ver Island and the greater Pacific Ocean beyond. We have been growing deciduous magnolias successfully for nearly 30 years in the David C. Lam Asian Garden. Some individuals of Magnolia campbellii, M. campbel-lii subsp. mollicomata and M. sargentiana var. robusta have grown to nearly 20m and are covered with blooms nearly every spring. This paper is restricted to evergreen magnolias, an intriguing group of species from China and northern Vietnam that have become established in the Asian Garden over the last 18 years. The works of Figlar and Nooteboom(2004), Kumar (2006), Liu (2004) , and Nooteboom (2000), plus the phylogenetic advances report-
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.197 | 0.100 |
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".