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Portable Electronic Nose for Detection of Spoiling Alaska Pink Salmon ( <i>Oncorhynchus gorbuscha</i> )

2006· article· en· W2070740481 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Food Science · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsCanadian Food Inspection Agency
FundersDivision of Ocean SciencesAlaska Sea Grant, University of Alaska Fairbanks
KeywordsSlushOncorhynchusFish <Actinopterygii>Electronic noseFisheryFood spoilageAnimal scienceBiologyEnvironmental scienceMeteorologyGeographyBacteria

Abstract

fetched live from OpenAlex

ABSTRACT: The ability of a portable hand‐held electronic nose (EN) in detecting spoilage of whole Alaska pink salmon ( Oncorhynchus gorbuscha ) stored at 14 °C and in slush ice (1 °C) was investigated. Fish were sampled daily at 14 °C for up to 3 d, while fish stored in slush ice were sampled at various intervals up to 16 d. Sensory evaluations indicated that fish were rejected at day 3 when stored at 14 °C and at day 12 when stored in slush ice. Aerobic bacteria counts for fish skin at 14 °C ranged from 3.4 log 10 colony‐forming units (CFU)/cm 2 (day 0) to 4.8 log 10 CFU/cm 2 (day 3) and for fish stored in slush ice ranged from 3.4 log 10 CFU/cm 2 (day 0) to 5.5 log 10 CFU/cm 2 (day 16). The correct classification rate using forward stepwise general discriminate analysis was 85% and 92% for EN analysis of belly cavity volatiles for fish held at 14 °C and in slush ice, respectively. A predictive model may be developed for spoilage of whole Alaska pink salmon by analyzing belly cavity odors using the EN.

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.

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 score0.039
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.215
Teacher spread0.208 · 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