Real-time PCR detection and discrimination of the <i>Ceratocystis coerulescens</i> complex and of the fungal species from the <i>Ceratocystis polonica</i> complex validated on pure cultures and bark beetle vectors
Bibliographic record
Abstract
Eight Ceratocystis Ellis & Halst. species belonging to the Ceratocystis coerulescens complex are pathogens causing blue-stain on Pinaceae. Three of these species, namely C. polonica, C. laricicola, and C. fujiensis, are particularly aggressive and can cause tree mortality. Although currently absent from the North American landscape, they are considered a significant potential threat to the Canadian boreal forest. As they are difficult to distinguish from native North American species belonging to the C. coerulescens complex, we developed a real-time PCR detection test for each of the three species to detect the equivalent of one fungal spore directly from insect vectors. DNA from at least one species of the C. coerulescens complex was detected on 86% of the beetles (Ips typographus (Linnaeus, 1758) and Ips cembrae (Heer, 1836)), whereas C. polonica DNA was detected on 60% of the I. typographus and C. laricicola DNA was detected on 84% of the I. cembrae. Between 20 and 344 225 spore equivalents were detected on the beetle specimens, and no inhibition effect of DNA extract from environmental samples was observed. These molecular detection tools will allow for rapid and reliable detection of C. polonica, C. laricicola, or C. fujiensis, allowing for a rapid implementation of eradication measures in case of introduction into Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".