Differentiation of <i>Tilletia</i> taxa by rep‐PCR genomic fingerprinting*
Bibliographic record
Abstract
The potential of repetitive‐sequence‐based polymcrase chain reaction (rep‐PCR) fingerprinting of fungal genomic DNA as a rapid and simple alternative to random amplified polymorphic DNA (RAPD) analysis in the study of phylogenetic relationships, and also as a diagnostic method, was investigated with species of Tilletia. DNA primers (BOX, ERIC and REP) corresponding to conserved repetitive element motifs, originally described in prokaryotes, were used to generate genomic fingerprints of T. indica, T. walkeri, T. controversa, T. laevis, T. tritici, T. goloskokovii, T. barclayana and members of the T. fusca complex. Computer‐assisted analysis of the database of combined fingerprints clearly distinguished each taxon and indicated phylogenetic relationships consistent with previously reported RAPD analyses. There were three main cluster groupings where isolates showed 35–40% similarity. Group 1 included T. indica and T. walkeri , group 2 included members of the T. fusca complex, as well as T. controversa, T. laevis, T. tritici and T. goloskokovii , and group 3 included only T. barclayana. If, as is likely, the conserved repetitive element motifs on which this technique is based are widespread or universal in fungal species, rep‐PCR shows strong potential, not only as a simple generic taxonomic tool, but also as a diagnostic method.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".