Colorimetric indicator films based on carboxymethyl cellulose and anthocyanins as a visual indicator for shrimp freshness tracking
Bibliographic record
Abstract
This study aimed to evaluate the response efficiency of colorimetric indicator films based on carboxymethyl cellulose (CMC) incorporated with different anthocyanins [Karanda alone (CMC/AK), butterfly pea alone (CMC/AB), and a mixture of anthocyanins from Karanda and butterfly pea (CMC/AK75/AB25)] for tracking shrimp freshness during storage at different temperatures and times (4 °C for 8 days and 25 °C for 30 h). The mathematical models were also applied to predict their freshness and shelf life. The CMC/AK75/AB25 indicator film was the most sensitive and clearly changed color, which could be distinguished by the naked eye. Color changes indicated the shrimp deterioration processes: dark purple (fresh), purplish gray or gray (semi-fresh), and olive green or brown (spoilage). During shrimp storage at temperatures of 4 and 25 °C, the pH reached 7.52 and 8.14, TVB-N 35.98 and 72.72 mg/100 g, and TVC 5.75 and 7.88 log CFU/g, respectively, indicating shrimp had completely deteriorated. Furthermore, there was a positive correlation between the ΔE value of the indicator film and both TVB-N and TVC. These findings suggest that the CMC/AK75/AB25 indicator film could serve as a real-time visual indicator for tracking shrimp freshness and could enhance the guarantee of shrimp safety.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".