Bibliographic record
Abstract
The 140 000 or so fungal species reported so far are heterogeneously defined based on varying criteria such as morphological, physiological, mating, and (or) molecular features. Incongruences are common among traits used to separating closely related species and it is often difficult to compare fungal taxonomic groups defined based on different species recognition criteria. Though DNA sequence-based classification and identification have been made, a consensus has not been reached, primarily due to intrinsic limitations in the proposed one or a few genes. Here, I argue that the fundamental reason for the observed inconsistencies is that speciation is a stochastic process with the emergence and fixation of different traits influenced differently by many non-deterministic factors such as population size, random mutation, mode(s) of reproduction, selection imposed by interacting biotic and abiotic factors, and chance events. Each species concept attempts to capture one or a few traits emerged in the continuous process of speciation. I propose that a genome sequence-based classification and identification system could unify and stabilize fungal taxonomy and help integrate taxonomy with other fields of fungal biology. The genomic species concept could be similarly argued for other groups of eukaryotic microbes as well as for plants and animals.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".