Practical methods for estimating the infection rate of <i>Quercus robur</i> acorn seedlots by <i>Ciboria batschiana</i>
Bibliographic record
Abstract
Summary The pathogenic fungus, Ciboria batschiana infects acorns prior to fall collection and if they are not freed of the fungus by thermotherapy seedlots can suffer serious losses during subsequent storage. However, since thermotherapy is time‐consuming and expensive, and sometimes has undesirable side‐effects, its use is not justified without knowing if and how intensively a seedlot is infected. It is demonstrated here that typical lesions on the surface of the cotyledons are a reliable indicator of infection by C. batschiana and that a method based on mycelium development on incubated cotyledons allows C. batschiana infection levels to be determined within 1–2 weeks. There were no significant differences in estimated C. batschiana infection levels between the visual assessment of the lesions before the incubation and the visual assessment of outgrowing mycelium from these lesions after the incubation. Using one or both of the described methods a decision can be made on the necessity for thermotherapy of acorn seedlots, i.e. before nursery sowing or long‐term, cold storage. The test based on mycelium development on incubated cotyledons can also be used for quality control following thermotherapy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".