Bibliographic record
Abstract
Abstract Batch propionic acid fermentation kinetics was studied using five different initial concentrations of lactose (i.e., 37 g/L, 45g/L, 50g/L, 57 g/L and 73 g/L) at constant temperature (30°C) and pH (6.5) under anaerobic conditions using Propionibacterium acidipropionici (ATCC 4875). When the initial substrate concentration was 37 g/L, 45 g/L, 50 g/L, 57 g/L and 73 g/L, then, correspondingly, 16 g/L, 19 g/L, 22.25 g/L, 25.3 g/L and 26.3 g/L of propionic acid was accumulated in the fermentation broth. Increasing the supply of lactose in the fermentation medium led to the accumulation of by products succinate, acetate and pyruvate. Maximum propionate yield (0.44 g/g) and comparatively lesser impurities (byproducts) were achieved with 57 g/L initial lactose concentration. The batch growth kinetics was eventually used to develop and test a mathematical model for propionic acid fermentation by P. acidipropionici at pH 6.5 and S o = 57 g/L. Y X/S max was found to be the most sensitive parameter of the model. The same model also successfully simulated the batch kinetics observed at S o = 37 g/L. However the model failed to simulate the fermentation kinetics observed at S o = 73 g/L. The developed model can be used for process optimization studies.
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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 | 0.000 | 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".