Assembling the fungal tree of life: progress, classification, and evolution of subcellular traits
Bibliographic record
Abstract
Based on an overview of progress in molecular systematics of the true fungi (Fungi/Eumycota) since 1990, little overlap was found among single-locus data matrices, which explains why no large-scale multilocus phylogenetic analysis had been undertaken to reveal deep relationships among fungi. As part of the project "Assembling the Fungal Tree of Life" (AFTOL), results of four Bayesian analyses are reported with complementary bootstrap assessment of phylogenetic confidence based on (1) a combined two-locus data set (nucSSU and nucLSU rDNA) with 558 species representing all traditionally recognized fungal phyla (Ascomycota, Basidiomycota, Chytridiomycota, Zygomycota) and the Glomeromycota, (2) a combined three-locus data set (nucSSU, nucLSU, and mitSSU rDNA) with 236 species, (3) a combined three-locus data set (nucSSU, nucLSU rDNA, and RPB2) with 157 species, and (4) a combined four-locus data set (nucSSU, nucLSU, mitSSU rDNA, and RPB2) with 103 species. Because of the lack of complementarity among single-locus data sets, the last three analyses included only members of the Ascomycota and Basidiomycota. The four-locus analysis resolved multiple deep relationships within the Ascomycota and Basidiomycota that were not revealed previously or that received only weak support in previous studies. The impact of this newly discovered phylogenetic structure on supraordinal classifications is discussed. Based on these results and reanalysis of subcellular data, current knowledge of the evolution of septal features of fungal hyphae is synthesized, and a preliminary reassessment of ascomal evolution is presented. Based on previously unpublished data and sequences from GenBank, this study provides a phylogenetic synthesis for the Fungi and a framework for future phylogenetic studies on fungi.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".