Effects of Seed Soaking with Four Chemical Reagents on Seed Vigor and Seedling Growth in Tobacco(Nicotiana tabacum L.)
Bibliographic record
Abstract
The study was performed to explore the effects of different soaking treatments on seed vigor and seedling growth of tobacco cv.Yunyan 203 and MS Yunyan 85.The germination,seedling growth,protective enzymes activities and the content of MDA were tested after seed soaking treatments with different concentrations of brassiolins(BR),gibberellins(GA),salicylic acid(SA) and CaCl2.The results showed that the best concentration for each reagent were 1.0 mg/L BR,50 mg/L GA,120 mg/L SA and 10 mg/L CaCl2,the four treatments could improve the germination energy,germination percentage,germination index and decrease the content of MDA.Among all the treatments,1.0 mg/L BR and 50 mg/L GA were the most effective treatments to improve seed vigor and seedling growth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".