Fermentation of Glucose and Xylose to Hydrogen in the Presence of Long Chain Fatt y Acids
Bibliographic record
Abstract
Hydrogen is a clean, efficient and versatile energy source which makes it a suitable alternative to fossil fuels. Mixed anaerobic cultures has the potential to produce hydrogen in a sustainable way in methanogenic bacteria can be inhibited. Batch studies were performed to assess the fermentation of glucose and xylose individually and together to observe if the sugar mixture is effective in hydrogen fermentation. Experiments were performed using a variety of LCFAs in order to inhibit methanogens so hydrogen can be collected. The highest amount of hydrogen produced took place in cultures fed LA plus xylose, glucose and the 50%/50% sugar mixture with yields of 2.13+-0.05, 2.46+-0.19 and 2.32+-0.17 mol H2/mol sugar, respectively. The maximum yields generated on a mol hydrogen per mass of sugar was 13.65, 14.20 and 14.08 mmol H2/g sugar for the respective sugars fermented. The final results showed that the ratio of the two different sugars did not have a significant difference in the hydrogen yield.
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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) | 0.000 | 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".