Fungal species: thoughts on their recognition, maintenance and selection
Bibliographic record
Abstract
When it comes to fungal species and speciation, it is hard to find anything to say that has not already been said in several excellent recent reviews. The most comprehensive source of information is Burnett's recent book (Burnett, 2003), which expands upon the themes from his British Mycological Society Presidential Address (Burnett, 1983). In addition to reviewing mycological species concepts and speciation, he describes enough about basic mycology and the methodology of evolutionary studies to make chapters on defining fungal individuals and populations, or on the processes of evolution in fungi, useful for mycologists interested in evolution and for evolutionary biologists interested in fungi. Burnett's review of the early literature in fungal speciation is particularly helpful in the present age, when it seems as if literature that is not online is forgotten. A second source of information is Brasier (1997), who explored three of what he considered to be the four main elements contributing to fungal speciation: original interbreeding populations, natural selection on populations and reproductive isolation between populations. He left a discussion of mating systems to others. Brasier's discussion of natural selection is particularly good, and his figure comparing the narrow range of growth rates of dikaryotic hyphae taken from Schizophyllum commune fruiting bodies to the much broader range of growth rates for dikaryons synthesized from their haploid progeny is as clear a demonstration of the effects of selection as one could want.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.006 | 0.018 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".