Susceptibility of endophyte-infected grasses to winter pathogens (snow molds)
Bibliographic record
Abstract
Neotyphodium endophytes are suggested to be mutualistic symbionts of grasses and regarded as potential biological plant protection agents. We examined the effects of the Neotyphodium endophyte of meadow ryegrass on snow molds in vitro with dual cultures of endophyte and Typhula ishikariensis , and on grass–snow mold interactions in vivo in a greenhouse and in a field experiment. In dual cultures, the endophytes formed an inhibition zone and retarded the growth of T. ishikariensis. In the field experiment, however, the endophyte-infected (E+) meadow ryegrasses were more susceptible to T. ishikariensis than the endophyte-free (E–) grasses. Endophyte infection increased the winter damage of grasses both in greenhouse and in field conditions. After winter, the growth of E+ grasses exceeded the growth of E– plants in the field experiment, indicating the marked tolerance of E+ grasses against winter damage. We detected differences in growth and pathogenesis between the different T. ishikariensis strains and found meadow ryegrass cultivar–endophyte status interaction in the growth of meadow ryegrasses, which highlight the effects of the genetic background of the participants on endophyte–grass–snow mold interactions.
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 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) | 0.001 | 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".