Bibliographic record
Abstract
Abstract Oxidation of unsaturated lipids is a major cause of food quality deterioration by giving rise to the development of off‐flavor compounds and loss of nutritional value of food products. Although it has been known for a long time that lipid oxidation can be induced by catalytic systems such as light, temperature, enzymes, metals, and metalloproteins; the mechanism of oxidation reactions remained uncertain until the 1940s when free radicals and reactive oxygen species were found to be involved in oxidation processes by the pioneering work of Farmer et al. Furthermore, antioxidants were found to protect lipids against oxidation either by quenching free radicals or scavenging oxygen, among others. Antioxidants are substances that, when present in foods at low concentrations compared with that of an oxidizable substrate, markedly delay or prevent the oxidation of the substrate. Antioxidants that fit in this definition include free radical scavengers, inactivators of peroxides, and other reactive oxygen species (ROS), chelators of metals, and quenchers of secondary lipid oxidation products that produce rancid odors. Antioxidants have also been used in the health‐related area because of their ability to protect the body against damage caused by ROS as well as reactive nitrogen species (RNS) and those of reactive chlorine species (RCS).
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.065 | 0.036 |
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".