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Record W1992783364 · doi:10.3136/fstr.16.421

Evaluation of Quantitative PCR Methods for Genetically Modified Maize (MON863, NK603, TC1507 and T25)

2010· article· en· W1992783364 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

VenueFood Science and Technology Research · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsOxford Frozen Foods (Canada)
FundersKorea Food and Drug AdministrationInstitut National de la Recherche Agronomique
KeywordsGenetically modified maizePrismBiologyGenetically modified cropsGeneticsPhysics

Abstract

fetched live from OpenAlex

Novel real-time PCR-based quantitative methods were developed for three GM maize events; MON863, NK603 and TC1507. The quantitative methods were designed to amplify an event-specific segment for MON863 and NK603, and a construct-specific segment for TC1507. We also developed an event-specific quantitative method for T25. The conversion factor (Cf), which is required for calculating the GMO amount, was determined using three types of real-time PCR equipment; the ABI PRISM 7700,7900HT and 7500. The quantitative methods were evaluated by blind testing in an interlaboratory study using the ABI PRISM 7700 and 7900HT, and in a multilaboratory trial using the ABI PRISM 7500. The trueness, precision, and limit of quantitation were determined. Although the biases expressing the trueness for MON863, TC1507, and T25 were slightly high, all the data suggested that the developed methods were suitable for identification and quantification of these GM maize events.

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)0.021
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
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 score0.298
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.233
GPT teacher head0.466
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