Rhabdocline needle cast — most recent findings of the occurrence of <i>Rhabdocline pseudotsugae</i> in Douglas-fir seeds
Bibliographic record
Abstract
Rhabdocline pseudotsugae Syd. is one of the major fungal pathogens in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco). To date, macroscopic and microscopic analyses of disease symptoms have resulted in the description of the Rhabdocline needle cast pathogen as a highly specialized needle parasite. In practice, the parasite has traditionally been identified by its fruiting bodies on infected needles. But nevertheless, it is not possible to detect the fungus if typical morphological traits are absent. Polymerase chain reaction (PCR) based techniques facilitate the detection of even small quantities of fungal DNA, regardless of the existence of visible fungal structures. Recent investigations into paths of infection and distribution using PCR have identified R. pseudotsugae in various types of Douglas-fir tissue including embryonic tissue which did not exhibit any symptoms. Taking these findings as a basis, the present study systematically tested seeds from five German, 13 North American, and two Ukrainian areas of origin for infection with R. pseudotsugae. The fungus was definitively detected in samples from five German and seven North American areas of origin. Nineteen percent of the tested seeds were infected. This indicates that infected seeds might represent another potential source of infection in addition to the ascospore-based distribution of R. pseudotsugae.
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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 | 0.000 | 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 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".