Estimating Shelf Life of Anchovy Savory Chips Based on Sensory and Microbes Data Using the Arrhenius ASLT Method
Bibliographic record
Abstract
Savory fish chip is one of the fish-based snacks with additional.One of the problems that often occur in chip products is that excessive oil absorption during the frying process can cause changes in texture and rancidity after storage.Based on these problems, it is necessary to test the shelf life of savory fish chip products as a preventive step to ensure they remain viable.Therefore, this study aims to estimate the shelf life of anchovy savory chip products using the ASLT Arrhenius method.Shelf-life testing was carried out by storing the product in polypropylene plastic and given vacuum and non-vacuum treatments then stored at three different temperatures, 30, 40, and 50℃ for 6 weeks.At each week, chemical (fat content, free fatty acids, moisture content), physical (crispness), sensory (taste, odor, appearance, texture), and microbiological were tested.After being tested, it was found that the shelf life of anchovy savory chips in non-vacuum polypropylene plastic packaging was 50 days at 30℃.Meanwhile, the shelf life in polypropylene plastic packaging under vacuum conditions is 82 days at 30℃.This information suggests anchovy savory chips should be stored in polypropylene plastic packaging with vacuum conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".