Best practices and methods for telial and aecial host inoculations with <i>Cronartium ribicola</i> , causal agent of white pine blister rust
Bibliographic record
Abstract
Forest pathologists and tree breeders working with obligate biotrophs, such as rust fungi, depend on effective inoculation protocols for their studies. These protocols are crucial for advancing the understanding of pathogen biology and for selecting disease-resistant hosts. Over a century of research on the white pine blister rust pathogen, Cronartium ribicola, has greatly enhanced our knowledge of the optimal conditions for its collection, preservation and host inoculation. However, since C. ribicola cycles between two phylogenetically distinct hosts, research often focuses on only one part of the lifecycle, leading to the scattering of information on inoculation conditions and techniques across numerous studies. Additionally, evolving insights into C. ribicola biology have led to changes in methods over time, resulting in a variety of inoculation protocols for resistance screening programs and pathogen biology studies. Therefore, there is a need for an updated comprehensive framework that covers inoculation protocols for all critical life stages of C. ribicola. This review aims to consolidate decades of practical experience and scientific knowledge to provide valuable and adaptable information for future studies involving C. ribicola.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".