Bibliographic record
Abstract
Concepts and definitions of species have been debated by generations of biologists and remain controversial. Microbes pose a particular challenge because of their genetic diversity, asexual reproduction, and often promiscuous horizontal gene transfer (HGT). However, microbes also present an opportunity to study and understand speciation because of their rapid evolution, both in nature and in the lab, and small, easily sequenced genomes. Here, we review how microbial population genomics has enabled us to catch speciation "in the act" and how the results have challenged and enriched our concepts of species, with implications for all domains of life. We describe how recombination (including HGT and introgression) has shaped the genomes of nascent microbial, animal, and plant species and argue for a prominent role of natural selection in initiating and maintaining speciation. We ask how universal is the process of speciation across the tree of life, and what lessons can be drawn from microbes? Comparative genomics showing the extent of HGT in natural populations certainly jeopardizes the relevance of vertical descent (i.e., the species tree) in speciation. Nevertheless, we conclude that species do indeed exist as clusters of genetic and ecological similarity and that speciation is driven primarily by natural selection, regardless of the balance between horizontal and vertical descent.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".