<i>Chrysomyxa weirii</i> on Colorado Blue Spruce in Wisconsin
Bibliographic record
Abstract
In early June 2002, yellow spots and bands with erumpent telia on previous year's needles of Colorado blue spruce (Picea pungens) were noted in landscape tree nurseries in both northern (Sawyer County) and southern (Dane County) Wisconsin. Many 1 to 2 m tall trees were symptomatic at each location. Based on the age of affected needles, time of year of telium development, and telial characteristics including the size and shape of teliospores, the pathogen was identified as Chrysomyxa weirii, the cause of Weir's cushion rust (1,2). Identification of the pathogen was confirmed by Dale Bergdahl, (School of Natural Resources, University of Vermont), who also observed basidiospores. C. weirii is an autoecious microcyclic rust pathogen known to affect P. englemanii, P. glauca, P. mariana, P. pungens, and P. sitchensis. Although this fungus has been reported in the western United States from the Black Hills of South Dakota to Washington State, in the eastern United States from the southern Appalachian Mountains (Tennessee and West Virginia) to Vermont, and in most Canadian provinces and territories (1,2), to our knowledge, this is the first report from the Great Lakes Region of the United States. The occurrence of Weir's cushion rust in Wisconsin has direct implications for the economically important nursery and Christmas tree industry in this region. References: (1) D. Bergdahl and D. Smeltzer. Plant Dis. 67:918, 1983. (2) W. Ziller. The Tree Rusts of Western Canada. Canadian Forestry Service, Victoria, BC, 1974.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".