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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 OpenAlexaff
Reona Takabatake, Satoshi Futo, Yasutaka Minegishi, Masatoshi Watai, Chihiro Sawada, Kôsuke Nakamura, Hiroshi Akiyama, Reiko Teshima, Satoshi Furui, Akihiro Hino, Kazumi Kitta

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.

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)0.018
metaresearch head score (Gemma)0.015
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: Methods · Consensus signal: Methods
Teacher disagreement score0.018
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.233
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

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
GenreMethods

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
Published2010
Admission routes1
Has abstractyes

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