A comparison of ITS and LSU nrDNA phylogenies of <i>Fulgensia</i> (Teloschistaceae, Lecanorales), a genus of lichenised ascomycetes
Bibliographic record
Abstract
The phylogeny of the lichen genus Fulgensia Massal. & De Not. (Teloschistaceae, Lecanorales) is analysed using maximum parsimony and neighbor joining analyses of nuclear ITS and partial large subunit nuclear ribosomal DNA (nrDNA) sequences. Three matrices were analysed with maximum parsimony; an internal transcribed spacer nrDNA matrix, a large subunit nrDNA matrix, and a combined data set. The internal transcribed spacer region contributes 70% of the informative sites to the combined data set. The topology of the trees resulting from the analysis of the internal transcribed spacer region is identical to the tree topology resulting from the combined analysis, but it shows less resolution at basal parts of the tree. Two sites for putative spliceosomal introns in the large subunit nrDNA, at position 808 and 914 (relative to Saccharomyces cerevisiae) are reported. Fulgensia, as currently understood, is polyphyletic and some species have to be excluded. The molecular analyses identified groups of species within the genus that are also supported by anatomical and morphological characters. The results of the analyses are compared with existing classification concepts based on morphological and anatomical data.Key words: LSU, ITS, nrDNA, introns, Fulgensia, phylogeny.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".