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Record W2580034160 · doi:10.5740/jaoacint.16-0290

Detection, Enumeration, and Isolation of Vibrio parahaemolyticus and V. vulnificus from Seafood: Development of a Multidisciplinary Protocol

2016· article· en· W2580034160 on OpenAlexaff
Swapan K. Banerjee, Jeffrey M. Farber

Bibliographic record

VenueJournal of AOAC International · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsUniversity of GuelphHealth Canada
Fundersnot available
KeywordsVibrio vulnificusVibrio parahaemolyticusEnumerationMicrobiologyBiologyIsolation (microbiology)VibrioAgarContaminationAgar plateVibrionaceaeFood scienceBacteriaEcology

Abstract

fetched live from OpenAlex

Vibrio parahaemolyticus and V. vulnificus are bacterial foodborne pathogens that can cause illnesses in humans after ingestion or exposure to contaminated seafood or coastal waters. A procedure that combines microbiological, biochemical, and molecular methods was designed and optimized for the detection, enumeration, isolation, and characterization of these clinically significant Vibrio spp. Initially, microbiological culturing is used to resuscitate and isolate presumptive Vibrio spp. from chilled seafood samples. Biochemical tests are then used to analyze and select presumptive isolates at the species level, and, lastly, molecular methods, such as PCR targeting species-specific hemolysin genes, are used to confirm identification and assess the potential pathogenicity of presumptive isolates. By using artificially contaminated molluscan homogenates with known numbers of V. parahaemolyticus, this method yielded, on average, 90% recovery on complete agar media and 88% recovery on selective media. For V. vulnificus, the recovery rates were 86% (complete media) and 84% (selective media). Linearity of recovery of Vibrio spp. from artificially contaminated seafood homogenates supported the applicability of this method. Overall, this performance-tested protocol is easy to use, cost-effective, and fit-for-purpose, with potential for routine use in basic microbiological facilities.

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 score0.167
Threshold uncertainty score0.200

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 head0.012
GPT teacher head0.297
Teacher spread0.285 · 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

Citations20
Published2016
Admission routes1
Has abstractyes

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