Barley
Bibliographic record
Abstract
Abstract The value of barley ( Hordeum vulgare L.) has steadily gained importance over the years. The economic and consumer importance of barley is constantly being re‐evaluated as new market niches and end‐uses become evident. Improvement strategies have generally employed conventional breeding methods, including mutation‐breeding approaches. However newer technology‐driven improvement strategies offer promising new perspectives and include genetic transformation. Barley was generally recalcitrant to tissue culture and transformation, but is now fairly amenable to genetic transformation by particle bombardment as well as by Agrobacterium . Target traits for modification have encompassed malting, nutritional and disease‐resistance attributes in barley. However, with the emerging trends in high‐throughput genomic sequencing and the need for functional validation of cloned genes, genetic transformation of barley has become an important tool and use of approaches such as transposable elements mediated transformation offers the possibility of producing large numbers of transgenic barley plants. Approaches based on the RNAi technology are also likely to advance understanding of the functions of cloned genes in barley. In this chapter, there is a wide‐ranging discussion on barley genetic transformation, prospects, challenges and risk assessment and environmental concerns.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.148 | 0.140 |
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".