Molecular Detection of <i>Phytophthora ramorum</i> by Real-Time Polymerase Chain Reaction Using TaqMan, SYBR Green, and Molecular Beacons
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.
Bibliographic record
Abstract
ABSTRACT Sudden oak death, caused by Phytophthora ramorum, is a severe disease that affects many species of trees and shrubs. This pathogen is spreading rapidly and quarantine measures are currently in place to prevent dissemination to areas that were previously free of the pathogen. Molecular assays that rapidly detect and identify P. ramorum frequently fail to reliably distinguish between P. ramorum and closely related species. To overcome this problem and to provide additional assays to increase confidence, internal transcribed spacer (ITS), beta-tubulin, and elicitin gene regions were sequenced and searched for polymorphisms in a collection of Phytophthora spp. Three different reporter technologies were compared: molecular beacons, TaqMan, and SYBR Green. The assays differentiated P. ramorum from the 65 species of Phytophthora tested. The assays developed were also used with DNA extracts from 48 infected and uninfected plant samples. All environmental samples from which P. ramorum was isolated by PARP-V8 were detected using all three real-time PCR assays. However, 24% of the samples yielded positive real-time PCR assays but no P. ramorum cultures, but sequence analysis of the coxI and II spacer region confirmed the presence of the pathogen in most samples. The assays based on detection of the ITS and elicitin regions using TaqMan tended to have lower cycle threshold values than those using beta-tubulin and seemed to be more sensitive.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it