Abiotic Stress and Plant Genome Evolution. Search for New Models
Bibliographic record
Abstract
The remarkable ability of plants to adapt to many different adverse environments is a fascinating process. Research into the physiology and metabolism of so-called extremophiles not only fosters better understanding of the evolutionary processes that have created the diversity of life as it exists on earth, but also has economic implications for agricultural biotechnology and the development of novel products. The capacity to sequence genomes and the availability of novel molecular tools have now catapulted biological research into eras of genomics and post-genomics, creating an opportunity to apply genomic techniques to extremophile models. This has led plant scientists to search for such models among the relatives of Arabidopsis (Arabidopsis thaliana), the most universally used species in molecular plant research owing to its many technical advantages and the wealth of available biological information. A workshop held in Paris in September 2004 united scientists from the United States, Canada, Japan, Israel, and Europe under the header Integrating International Research on Plant Abiotic Stress Tolerance Using Arabidopsis Relative Model Systems (ARMS): Thellungiella halophila. The aim of this Biotechnology and Biological Sciences Research Council (BBSRC)-funded meeting, coorganized by Anna Amtmann (University of Glasgow, UK) and Arnould Savouré (University of Paris VI, France), was to explore the use of Thellungiella as a model extremophile and to develop strategies for its development by the international community.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".