A study on High Density Increasing Formention of Lactobacillus plantarum
Bibliographic record
Abstract
In order to develop new style microecological preparation,the condition of improving the production level for Lactobacillus plantarum were screened and optimized.The single factor experiments and response surface analysis were carried out to determinate the optimal proportion of ingredient of fermentation medium.And then,the large-scale culture technology and the Lp-2 culture process was screened and optimized.The maximum yields of Lactobacillus plantarum can be obtained under conditions of sucrose,29 g/L,yeast extract,31g/L,peptone,25g/L,K2HPO4 20 g/L,NaAc,6 g/L,Di-Ammoniun Hydrogen Citrate,2 g/L,tween80,2 g/L,MgSO4,0.1 g/L,MnSO40.1g/L at speed 100 r/min,32℃ for 9.6 h in a 3-ton fermentor.The maximum yields of Lactobacillus plantarum was 1010 CFU/mL.The result showed that our culture optimization is obvious,and it is worth being populalized and applied.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".