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Record W1969209671 · doi:10.1021/jf011606p

Detection of Genetically Modified Coho Salmon Using Polymerase Chain Reaction (PCR) Amplification

2002· article· en· W1969209671 on OpenAlexaff
Saad A. Masri, Heidi Rast, Teresa Ripley, D. James, Margaret Green, Xiaoyan Jia, Robert H. Devlin

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsFisheries and Oceans CanadaHealth Canada
Fundersnot available
KeywordsPolymerase chain reactionPrimer (cosmetics)Genetically modified organismBetaineChromatographyPrimer dimerBiologyTransgeneMolecular biologyDNADNA extractionReal-time polymerase chain reactionChemistryMultiplex polymerase chain reactionGeneBiochemistry

Abstract

fetched live from OpenAlex

A PCR-based protocol for the identification of genetically modified salmon carrying a growth hormone transgene was developed. Several primer pairs were examined, and the primers that gave consistent results were selected to conduct routine testing. Comparison among several DNA extraction procedures, as well as different buffer compositions, led to the adoption of TriZol as the method of choice. Low potassium and high magnesium chloride concentrations were very important in the overall success of the PCR reaction, whereas buffer pH, ranging from 8.3 to 9.2, had little impact on the amplification reaction. The optimal primer annealing temperature was 52 degrees C. Although fish muscle tissues were the primary source for DNA samples, detection of the transgene was also possible in bones, skin, fins, and other organs. No benefits were achieved by the addition of additives such as dimethyl sulfoxide and betaine to the PCR reaction. This optimized PCR method was used to identify all samples tested (61 samples and 17 controls) with 100% accuracy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2002
Admission routes1
Has abstractyes

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