Spatial and temporal dynamics<i>of Puccinia andropogonis</i>on<i>Comandra umbellata</i>and<i>Andropogon gerardii</i>in a native prairie
Bibliographic record
Abstract
The rust Puccinia andropogonis (Schwein.) was studied on its aecial and telial plant hosts, comandra ( Comandra umbellata L. Nutt.) and big bluestem ( Andropogon gerardii Vitman), respectively, in a native prairie to investigate the influence of aecial host proximity on disease severity of the telial host in a natural system. Both hosts were mapped to measure distances from comandra clones to selected big bluestem plants in a Minnesota prairie. Mean rust severity on big bluestem was regressed on the number of aecia on comandra (aecial density) within eight distance intervals from big bluestem plants. Distance intervals were analyzed both inclusive and exclusive of other distance intervals. There was a significant positive relationship between aecial density on comandra and rust severity on big bluestem that decreased with increasing distance in accordance with the power law model, becoming nonsignificant at distances >40 m. To establish whether the genetic background of big bluestem influenced the relationship between rust severity and the distance to comandra, a common garden was planted with a representative big bluestem plant population. The low coefficient of determination (r2) between mean rust severities of individual plants from one year to another suggests there is not a strong genetic component in the host determining disease severity.
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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".