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Record W2022649351 · doi:10.1271/bbb.70683

A Real-Time Quantitative PCR Detection Method for Pork, Chicken, Beef, Mutton, and Horseflesh in Foods

2007· article· en· W2022649351 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

VenueBioscience Biotechnology and Biochemistry · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsConestoga Meat Packers (Canada)
Fundersnot available
KeywordsTaqManDetection limitMitochondrial DNAMinor grooveCytochrome bFood scienceReal-time polymerase chain reactionBiologyMatrix (chemical analysis)DNAChemistryChromatographyGeneGenetics

Abstract

fetched live from OpenAlex

A rapid real-time quantitative PCR method to detect trace amounts of pork, chicken, beef, mutton, and horseflesh in foods was developed. The primers and TaqMan MGB (minor groove binder) probes were designed on the gene encoding cytochrome b for the specific detection of each species. The limit of quantification of this method was found to be 100 fg/microl of each mitochondrial DNA in 10 ng/microl of the wheat mitochondrial DNA matrix. The calculated R(2) values of the standard curves for the five species ranged between 0.994 and 0.999. This method would be particularly useful in the detection of hidden meat mince in processed foods, which would verify food labeling and gain consumers' trust.

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)0.001
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 score0.012
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.313
Teacher spread0.298 · 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