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CLOTH‐BASED HYBRIDIZATION ARRAY SYSTEM FOR DETECTION OF TOXIN GENES ASSOCIATED WITH MAJOR FOODBORNE PATHOGENIC BACTERIA

2005· article· en· W2081503246 on OpenAlexaff
Martine Gauthier, Burton W. Blais

Bibliographic record

VenueJournal of Rapid Methods & Automation in Microbiology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsMicrobiologyBiologyAmpliconBacteriaVibrio choleraeSalmonellaToxinMultiplex polymerase chain reactionEnterotoxinEscherichia coliPolymerase chain reactionCholera toxinPathogenic bacteriaVibrioGeneGenetics

Abstract

fetched live from OpenAlex

ABSTRACT A simple cloth‐based hybridization array system (CHAS) was developed for the identification of toxin genes associated with major foodborne pathogenic bacteria, including toxigenic Escherichia coli, Vibrio cholerae and Salmonella spp. Bacterial isolates were subjected to a multiplex polymerase chain reaction incorporating digoxigenin (DIG)–deoxyuridine triphosphate and primers targeting a variety of toxin genes (verotoxin, Salmonella enterotoxin, cholera toxin and heat‐labile/stable enterotoxin), followed by hybridization of the amplicons with an array of probes immobilized on polyester cloth and subsequent immunoenzymatic assay of the bound DIG label. This system provided sensitive and specific detection of the different target toxin gene markers in a variety of bacterial isolates, exhibiting the expected patterns of reactivity with a panel of bacteria having defined toxigenicity profiles. The CHAS is a cost‐effective tool facilitating the determination of the potential toxigenic profile of bacteria in the food microbiology laboratory, thus contributing valuable information to the risk‐assessment process in the microbiological analysis of foods.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.117
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.014
GPT teacher head0.303
Teacher spread0.289 · 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

Citations4
Published2005
Admission routes1
Has abstractyes

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