Abiotic stress tolerance of kikuyu (Cenchrus clandestinus) and some related grasses and potential of kikuyu for agricultural and urban environments
Bibliographic record
Abstract
The introduction of kikuyu (Cenchrus clandestinus (Hochst. ex Chiov.) Morrone) into Australia in 1918 has seen it become established and adapted to several geographic regions in a wide range of ecologies and environmental situations. After it naturalised to local conditions, researchers and farmers recognised the value of kikuyu in marginal and previously unproductive sites, where forage quality and quantity made this species popular with dairy farmers and pastoralists. Its versatility and prostrate, mat-forming characteristics also led to the adoption of kikuyu by local governments, homeowners and sporting organisations in urban environments as turf. Kikuyu has the ability to alleviate soil contamination and remediate soils, thus enhancing the use of previously unproductive land. However, the aggressive growth habit of the species, considered a problem in certain regions of the world, has led to a noxious weed classification in some states of the USA. This review includes information on expected changes to world agricultural and urban environments and the potential expanded role of kikuyu. The origin of kikuyu grass, genetic variability, tolerances to soil salinity and drought, and potential for genetic improvement are also discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".