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Modeling of Carbonated Metabolites Production by Clostridium butyricum W5 Under Anaerobic Conditions for Optimization of Hydrogen Metabolic Production

2012· article· en· W2152031922 on OpenAlexvenueno aff
Andres Camilo Diaz Valencia, G. Fajardo, Fabio Emiro Sierra Vargas, Carlos Alberto Guerrero Fajardo

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2012
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsnot available
FundersUniversidad Nacional de Colombia
KeywordsClostridium butyricumHydrogen productionBiochemical engineeringMicroorganismProduction (economics)Pulp and paper industryAnaerobic digestionHydrogenProcess (computing)Computer scienceEnvironmental scienceProcess engineeringChemistryBacteriaBiologyFood scienceMethaneEcologyEngineeringFermentation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.231
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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