Quality Indicators of Cultured Newfoundland Blue Mussels <i>(Mytilus edulis</i>) during Storage on Ice: Microbial Growth, pH, Lipid Oxidation, Chemical Composition Characteristics, and Microbial Fatty Acid Contents
Bibliographic record
Abstract
To devise proper strategies to evaluate and maintain the quality of cultured blue mussels (Mytilus edulis) during storage on ice, this study examined the potential use of microbial growth, pH, lipid oxidation, and composition characteristics as quality indicators. It also evaluated the use of individual (i15:0, ai15:0, i16:0, ai16:0, i17:0, ai17:0, 17:0) and total bacterial fatty acid contents as a rapid method to examine the microbial quality of stored mussels. Linear regression analyses of the storage period of mussels vs various quality indicators indicated that the strongest correlation was between the storage period and microbial growth (r = 0.973, p < 0.0001) followed by the microbial fatty acid ai15:0 content (r = 0.903, p < 0.0001) and ash content (r = 0.819, p = 0.0002). All other correlations between the storage period and quality indicators were moderate (r = 0.500-0.700 and p < 0.05), poor (r < 0.500 and p > 0.05), or negative (r = -0.657 and p = 0.027).
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".