Influence of Pyrolytic and Aqueous-Phase Reactions on the Mechanism of Formation of Maillard Products
Bibliographic record
Abstract
The influence of the reaction phase on the mechanism of formation of Maillard products was studied by comparison of (13)C-label incorporation patterns of the common products formed in model systems consisting of labeled glycine and D-glucoses subjected to both pyrolysis and heating in aqueous solutions. Pyrolysis experiments were performed at 250 degrees C for 20 s, and aqueous model systems were heated in sealed vials for 3 h at 120 degrees C followed by GC/MS analysis. Label incorporation patterns of the following compounds were analyzed: cyclotene, furanmethanol, acetylpyrrole, 5-methyl-pyrrole, trimethylpyrazine, acetic acid, 3-hydroxy-2-butanone, 2,3-butanedione, and 2-methyl-4, 5-dihydro-3(2H)-furanone. Although pyrolysis reaction produced higher number of products, however, the major pathways of formation of variety of important Maillard products followed the same mechanism under both pyrolytic and aqueous systems. Furthermore, contrary to literature speculations, 2-methyl-4, 5-dihydro-3(2H)-furanone was shown to be formed by ring contraction of 2,3-dihydro-3,5-dihydroxy-6-methyl-4(H)-pyran-4-one, through benzilic acid rearrangement, followed by decarboxylation.
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 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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".