Single Nucleotide Polymorphism-Based Diagnostic System for Crop-Associated <i>Sclerotinia</i> Species
Bibliographic record
Abstract
A molecular diagnostic system using single nucleotide polymorphisms (SNPs) was developed to identify four Sclerotinia species: S. sclerotiorum (Lib.) de Bary, S. minor Jagger, S. trifoliorum Erikss., and the undescribed species Sclerotinia species 1. DNAs of samples are hybridized with each of five 15-bp oligonucleotide probes containing an SNP site midsequence unique to each species. For additional verification, hybridizations were performed using diagnostic single nucleotide substitutions at a 17-bp sequence of the calmodulin locus. The accuracy of these procedures was compared to that of a restriction fragment length polymorphism (RFLP) method based on Southern hybridizations of EcoRI-digested genomic DNA probed with the ribosomal DNA-containing plasmid probe pMF2, previously shown to differentiate S. sclerotiorum, S. minor, and S. trifoliorum. The efficiency of the SNP-based assay as a diagnostic test was evaluated in a blind screening of 48 Sclerotinia isolates from agricultural and wild hosts. One isolate of Botrytis cinerea was used as a negative control. The SNP-based assay accurately identified 96% of Sclerotinia isolates and could be performed faster than RFLP profiling using pMF2. This method shows promise for accurate, high-throughput species identification.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".