Study on Extraction of Polysaccharide from Dregs of Schisandra chinensis(Turcz. ) Bailey and of Seed Germination of Chinese cabbage
Bibliographic record
Abstract
To explored and optimized extraction process of polysaccharide from dregs of Schisandra chinensis and polysaccharide on the influence of seed germination of Chinese cabbage.Screen the influence of different extracting temperature,extracting time and solid/liquid ratio with levels,polysaccharides with different concentrations on the influence of seeds germination and growth.The results showed that extracting temperature had significant effect on the yield of polysaccharides,the influence of extracting time and solvent amount had no significant effect.The best extracting program for polysaccharides was extracting temperature 100 ℃,extracting time 2 h and solid/liquid ratio 1 ∶30(m/V).Polysaccharides with different concentrations all had different promotion of seed germination of Chinese cabbage,the highest germination rate and potential of seed were 89% and 53% respectively in 0.6 mg/mL of polysaccharides,radicals and germ growth better.The study had decided the optimum extracting process of polysaccharide from dregs of Schisandra chinensi,and the best concentration of polysaccharide for seeds germination and growth of Chinese cabbage.
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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) | 0.001 | 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) | 0.001 | 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".