Field occurrence and epidemic dynamics of alfalfa common leaf spot (Pseudopeziza medicaginis) in the mountain area of southern Ningxia
Bibliographic record
Abstract
Field Occurrence and epidemic dynamics of alfalfa common leaf spot (Pseudopeziza medicaginis) were investigated in the exotic and native varieties at different fields and clipping times. The results showed that the occurrence degree of alfalfa common leaf spot was different with varieties, but the trends of the disease were the same. Within 18 varieties, the highest disease incidence and index were found on Canadian DY and winter hardy alfalfa, the lowest ones found on Guyuan alfalfa, and those on American Zahua alfalfa, WL323, and Zhongmo No. 1 were the middle degree. The development of the disease exhibited a S type curve in seasonal dynamics. The disease began from the end of May to early June, and reached up to exponential phase in July and August, and declined in September. The increased velocity of the disease was the highest in the first and middle ten days of August, and the last ten days of both July and August took second place. The key period of the disease was in July and August. Clipping methods also affected the occurrence and development of the disease. Therefore, rational clipping methods at appropriate time were the available measures to decay, relieve, and control the alfalfa common leaf spot.
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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 | 0.001 | 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".