Research on rattans in China: Conservation, cultivation, distribution, ecology, growth, phenology, silviculture, systematic anatomy and tissue culture
Bibliographic record
Abstract
It has generally been assumed that rattan resources would be available for use for perpetuity. However, in the last two decades, these resources have dwindled, affecting the once flourishing furniture industry, as well as lowering the income of the tribal and rural people in many countries in the region, who gather and supply the material for the market. Most of the rattans used in trade and commerce are obtained from plants growing in the forests. Malaysia and Indonesia, the two major exporting countries, banned the export of raw rattan for some years, resulting in the decline of rattan supply. Consequently there were many imbalances in the international trade and furniture manufacturing industries were shut down in some countries. Foreseeing the uncertain future, IDRC of Canada, ODA of U.K., UNDP and FAO of U.N. started funding research projects as far back as 70s to promote large scale cultivation of rattan in Malaysia and Indonesia. Many new methods of cultivation were tested. In late 1980s, IDRC also supported rattan research projects in India, China, Indonesia and other countries. The results obtained from studies in China were published in 1994, in Chinese ”Research on Rattans in China”. This is a compendium of about 30 research papers with English summary for each paper. The first part of the volume includes rattan resources in China, their biology and ecology, nursery techniques and propagation, cultivation and utilization. The second part includes tissue culture work on rattan which has facilitated large scale production of plantlets of chosen species for plantation establishment. In vitro produced plants of many species are growing with in several plantations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".