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Record W2013173968 · doi:10.1139/b00-126

A comparison of ITS and LSU nrDNA phylogenies of <i>Fulgensia</i> (Teloschistaceae, Lecanorales), a genus of lichenised ascomycetes

2000· article· en· W2013173968 on OpenAlexvenueno aff
Thomas Kasalicky, Heidi Döring, Gerhard Rambold, Mats Wedin

Bibliographic record

VenueCanadian Journal of Botany · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
FundersNational Eye InstituteHong Kong Institute of Education
KeywordsInternal transcribed spacerBiologyMaximum parsimonyPolyphylyRibosomal DNAGenusPhylogeneticsEvolutionary biologyPhylogenetic treeGeneticsBotanyGeneClade

Abstract

fetched live from OpenAlex

The phylogeny of the lichen genus Fulgensia Massal. &amp; 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.228
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2000
Admission routes1
Has abstractyes

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