Bacteriophages in Industrial Food Processing: Incidence and Control in Industrial Fermentation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fermentation has been used as a method of food preservation for millennia. Some modern food fermentations are still initiated using the indigenous bacterial micro-flora of the raw substrate, also referred to as spontaneous fermentation. From the nutrient-rich environments to extreme environments such as the human digestive tract or deep-ocean thermal vents, bacteriophages have been discovered. Bacteriophages are undoubtedly the greatest threat in fermented food productions, especially in the dairy industry, which has openly acknowledged this biotechnological problem. Starter cultures used by the dairy industry are composed of lactic acid bacteria, which represent a diverse group including, among others, the genera Lactococcus and Lactobacillus as well as the species Streptococcus thermophilus. The bacteriophages infecting these groups of bacteria have been extensively characterized because of their negative impact on the industry. For example, lactococcal phages are the most-studied group of bacterial viruses after the Escherichia coli phages. Biochemical methods are based primarily on immunochemical assays and molecular detection of bacteriophage genetic material (most often double-stranded DNA). Biochemical detection techniques are essential in identifying an emerging phage population. Bacteriophage-insensitive mutants (BIMs) have the same genetic determinants and most likely the same desired metabolic properties as the wild-type strain. Bacterial restriction-modification (R-M) systems are recognized as among the first line of defense after foreign DNA entry into the cell. The emergence of resistant phages points to the necessity of continuing to identify new phage resistance mechanisms for long-term phage resistance in important bioindustries.
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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 | 0.001 | 0.001 |
| 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 it