Production of α-Glycerylphosphorylcholine and Other Compounds from Wheat Fermentation
Bibliographic record
Abstract
The liquified mash of milled grains from the Canadian wheat cultivar, AC Andrew, was fermented to determine whether α-glycerylphosphorylcholine (α-GPC) accumulated and whether the accumulation was dependent on fermentation-related factors. Fermentation was conducted at a temperature of 37 °C for 7 days (168 h) with samples collected every 24 h. The samples were analyzed using a proton nuclear magnetic resonance water suppression pulse sequence to allow the quantitation of ethanol, acetic acid, lactic acid, succinic acid, glycerol, phenethyl alcohol, betaine, and α-GPC. A Gompertz model was used to interpret fermentation kinetics for each analyte, and during fermentation, ethanol accumulated to a concentration of 72.1 g/L while α-GPC accumulated to a concentration of 1.68 g/L over 72 h. There were significant and positive correlations between the accumulation of α-GPC, ethanol, lactic acid, and glycerol and acetic acid production. Furthermore, there were no significant negative correlations between the productions of these compounds; hence, all the compounds accumulated during fermentation were produced simultaneously with no observed decrease measured in any compound. This indicates that α-GPC can be successfully produced industrially without any negative impact on ethanol or other useful compounds.
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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 | 0.001 |
| 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 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".