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Record W2032828946 · doi:10.1271/bbb.70662

Specific Discrimination of Chicken DNA from Other Poultry DNA in Processed Foods Using the Polymerase Chain Reaction

2008· article· en· W2032828946 on OpenAlex
T. Fujimura, Takashi Matsumoto, Soichi Tanabe, Fumiki Morimatsu

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 · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsConestoga Meat Packers (Canada)
FundersFujita Health University
KeywordsPrimer (cosmetics)Polymerase chain reactionDNAPrimer dimerBiologyMolecular biologygenomic DNAMitochondrial DNAProcessed meatMultiple displacement amplificationGeneFood scienceDNA extractionChemistryGeneticsMultiplex polymerase chain reaction

Abstract

fetched live from OpenAlex

In the present study, specific discrimination of chicken DNA contamination in processed foods using the polymerase chain reaction was investigated. The primer pair was designed to amplify a 102-bp fragment of the chicken mitochondrial 16S ribosomal RNA gene. While the DNA from chicken meat was amplified, the DNA from other poultry meat, mammalian meat, fish, shellfish, and cereals was not amplified. The primer amplified DNA fragments derived from model processed and nonprocessed food samples containing 0.001, 0.01, 0.1, 1, 10, and 100% chicken.

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 score0.006
Threshold uncertainty score0.420

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 studies0.0000.001
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 head0.028
GPT teacher head0.261
Teacher spread0.234 · 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