Seasonal fruiting and sporulation of Thekopsora and Chrysomyxa cone rusts in Norway spruce cones and alternate hosts in Finland
Bibliographic record
Abstract
The need to improve control of cone rust epidemics led us to investigate seasonal fruiting and sporulation of cone rusts in Norway spruce ( Picea abies (L.) Karst.) cones and alternate hosts in 2006–2008. Spermogonia of Chrysomyxa pirolata Wint. and aecia of Thekopsora areolata (Fr.) Magnus developed in current-year cones in June, whereas C. pirolata aecia developed and started to sporulate in July. Thekopsora areolata aecia sporulated mainly in previous-year cones in May–August. Uredinia, telia, and basidia of C. pirolata developed in overwintered Pyrola sp. and Orthilia secunda L. leaves in May and sporulated in May–June. Uredinia of T. areolata developed in current-year Prunus padus L. leaves in June and sporulated in June–August. Telia of T. areolata developed in late summer, but no basidia were observed in overwintered Prunus padus leaves in March–May. Only minor variation occurred at the time of fruiting and sporulation of cone rusts both among cones and leaves of alternate hosts. Periods of high daily rainfall in May coincided with the epidemic peaks during female flowering in 2006. Dry periods in May coincided with high C. pirolata uredinia and low telia production on alternate hosts. However, monthly rainfall during pollination did not explain the epidemic rust patterns in cones. Timing of disease control is discussed.
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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 | 0.000 | 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".