Research on Advance of Rice False Smut Ustilaginoidea virens (Cooke) Takah Worldwide: IV. Identification of Rice Resistance to RFS, Management and Prospection of RFS
Bibliographic record
Abstract
Technological issues in identification of rice resistance were discussed in this part, including inoculum and its preparation, inoculation concentration of inoculum, inoculation time and method. It is very difficult to control RFS, RFS can only prevent but not cure, i.e., to control the RFS only spray fungicides before symptomatic appearance (rice smut balls appeared) can achieve better control efficiency, while once the smut ball appeared it could not be controlled even the concentration of fungicides increase several times, or spraying multiple times. Therefore, in order to achieve better control efficiency to RFS, integratd control measures need to be adopted. The integratd control measures including agricultural control, rice resistant varieties application, cultivation techniques, fertilization and water management, and fungicides application is the last approach and emergency measure for controlling RFS.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".