Evaluation of Quantitative PCR Methods for Genetically Modified Maize (MON863, NK603, TC1507 and T25)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".