The importance of living collections for botanical research: Araceae as a case study
Bibliographic record
Abstract
Botanical gardens play a crucial role in botanical research by maintaining living collections of plants that serve educational and scientific purposes. This article examines the significance of living collections, using the Araceae family as a case study. Botanical gardens worldwide house diverse collections that contribute to studies in systematics, taxonomy, anatomy, morphology, floral biology, pollination ecology, phytochemistry, and medicine. The Araceae family, with its extensive diversity and distribution, provides an excellent model for comparative studies. Historical and contemporary research has utilized these collections to advance knowledge in specific areas. For instance, molecular systematics has benefited from these collections, as have studies on calcium oxalate crystal production, floral anatomy and development, pollen–ovule ratios, pollen viability, seed size and growth type, thermogenesis, and pollination syndromes. The article highlights the indispensable role of living collections in facilitating research that would be challenging to conduct solely in the field. It underscores the need for continued investment in botanical gardens to preserve their scientific and educational value, and outlines future research opportunities that living collections can offer.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".