MétaCan
Menu
Back to cohort
Record W2006302257 · doi:10.1021/jf050082g

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

2005· article· en· W2006302257 on OpenAlexaffabout
Muhammad Ahmad Khan, Christopher C. Parrish, Fereidoon Shahidi

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMytilusFood scienceComposition (language)Fatty acidBacterial growthBiologyChemical compositionLipid oxidationChemistryEcologyBiochemistryBacteriaAntioxidant

Abstract

fetched live from OpenAlex

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).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.216
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicMeat and Animal Product QualityFrench-language works237,207