Bibliographic record
Abstract
Royal Botanical Gardens, in Hamilton and Burlington, Ontario, Canada, is Canada’s largest botanical garden by area, owning 1,100 ha of gardens, parklands, and protected natural areas. For more than 80 years, Royal Botanical Gardens (RBG) has been making significant contributions to conservation, protecting and restoring its nature sanctuaries that serve as in situ habitat for hundreds of species, including more than 50 species listed nationally or provincially as at-risk. Ex situ conservation of large horticultural collections is preserving significant germplasm of cultural and economic significance. This is a significant role for plant collections, and RBG’s include many horticultural cultivars that are rare or found nowhere else. Sixty taxa listed by the International Union for the Conservation of Nature (IUCN) as being globally at risk or listed in CITES appendices are also held in the collections. In addition, RBG has been delivering plant conservation and environmental messaging to garden visitors and through educational programs since the 1940s. Since the 1970s, RBG has participated in regional, national, and global initiatives to organize the botanical garden community around conservation and sustainability goals. This chapter reviews the development of RBG and its programs and collections, recognizing that its unique character is the result of its founding, development, and geographic and social setting. The themes of the 16 Targets of the Global Strategy for Plant Conservation are used as a framework to characterize the contributions of this institution.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.333 | 0.119 |
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".