Modeling microbial growth and biosynthesis of medium chain length polyhydroxyalkanoate (PHA) by Pseudomonas putida LS46
Bibliographic record
Abstract
Among different types of thermoplastics, polyhydroxyalkanoates (PHAs) with different physical/mechanical and thermal properties are well known, as they are biodegradable, biocompatible, and non-toxic. However, the main drawback of PHA biosynthesis in large scale is the high cost of production. It is known that PHA production can be considerably increased under oxygen-limited conditions. In this study, growth and synthesis of medium chain length PHAs (mcl-PHAs) by Pseudomonas putida LS46 cultured with octanoic acid under oxygen-limited conditions in the batch mode was modeled. Four models including the Monod model incorporated Leudeking–Piret (MLP), the Moser model incorporated Leudeking–Piret (Moser-LP), the Logistic model incorporated Leudeking–Piret (LLP), and the Modified Logistic model incorporated Leudeking–Piret (MLLP) were investigated. Kinetic parameters of each model were calibrated by using the multi-objective optimization algorithm, Pareto Archived Dynamically Dimensioned Search (PA-DDS) by minimizing the sum of absolute error (SAE) for PHA production and growth simultaneously. Among the four models, MLP and Moser-LP models adequately represented the experimental data for oxygen limited conditions. In addition, the MLP and Moser-LP models could not adequately simulate PHA production under oxygen excess conditions. For growth, under oxygen excess conditions, this deviation was not very significant.
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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 | 0.001 | 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".