Major achievements in safflower breeding and future challenges.
Bibliographic record
Abstract
Arguably the most important safflower breeding achievements over the past half century have come from India and California. Breeding for disease resistance globally and medicinal uses of safflower as developed in China, warrant special attention. Gila, grown on more area than perhaps any other, needs special recognition. The recent major breakthroughs towards biotechnological uses of safflower, as well as long-time efforts at successful hybrid development, can be anticipated to result in major achievements of the future. No other country has had as much safflower research carried out as has India; nor has there been more safflower production over millennia than in India. The All India Coordinated Research Project on Oilseeds included safflower from the early 1970's, improving productivity greatly. Under the mentorship of P.F. Knowles, the University of California at Davis, has contributed more than any other single centre towards our understanding and knowledge of genetics and inheritance of Carthamus tinctorius L. Resistances to major safflower diseases have been developed in safflower cultivars and germplasm in various countries: resistances to alternaria, rust, phytophthora and sclerotinia head rot. Medicinal uses of safflower, while widespread in China for centuries, may spread around the world. Released in 1958, Gila provided more global production than any other cultivar. Biotechnology of safflower is being aggressively developed, both in Canada and in India. Major advances and utilizations can be expected in this field of research and development. While major breakthroughs in hybrid safflower have been largely elusive, globally speaking, the future holds promise for such techniques.
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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 | 0.012 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".