Modeling of Carbonated Metabolites Production by Clostridium butyricum W5 Under Anaerobic Conditions for Optimization of Hydrogen Metabolic Production
Bibliographic record
Abstract
Hydrogen production has been one of the most studied problematics nowadays because of the worldwide needs of change in energy sources for daily use, industrial use and laboratory use. In addition, we can also mention the importance of this energy sources to be clean, self-sustainable and of course profitable for the industry, that is the reason why in this work we studied one of the most common hydrogen-producer microorganisms, Clostridium butyricum. This bacterial specie was chosen because it's metabolic pathways have been widely studied and it's an easy-obtainable microorganism present in almost any kind of anaerobic environment such as some zones of soil, human intestines and others, in addition to that, we can also mention some other species for hydrogen production: Kleibsella pneumoniae and Citrobacter freundii which can also be used for the modelation process and the industrial process of production. In this work we developed a process model about the metabolic pathways of C. butyricum in order to understand the hydrogen production process and reveal the points where it can be optimized. Mainly, the model was designed so it could predict the comportment of the process in the exponential phase of growth of the bacteria. Stoichiometric analysis was performed in order to create theoretical curves of the production of hydrogen and other metabolites. Part of the study was performed based in experimental results exposed by other authors, the model was developed in JMCAD ( an open-source software for complex dynamic system modeling based in Java. The predicted results are comparable with the experimental ones as it can be seen in the results section, the R² of all the curves was (near) to 0,97 so we could ensure a close relation with the reality. Some suggestions in order to maintain the exponential phase of growth in the cultures of C. butyricum are exposed and explained further in the article.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".