Hybridization without guilt: gene flow and the biological species concept
Bibliographic record
Abstract
Studies of the genetics of speciation are fundamental to our understanding of its causes and consequences. A tacit assumption of speciation research is that species are real evolutionary units. Different species concepts place different emphases on properties of species and so have the potential to shift the focus of studies of speciation. At present, the genetics of speciation is effectively the genetics of reproductive isolation (Coyne & Orr, 1998). In this vein, Wu et al. have been at the forefront of endeavours to understand the genetic architecture of speciation. Based on this work, Wu now suggests that the biological species concept (BSC) is in need of a major revision and rejects the current focus of speciation research on reproductive isolation (RI). Wu prefers to view RI as an epiphenomenon of secondary interest. We feel that this rejection of RI is unnecessary and overly restrictive, and generally that any modification of the BSC is premature given our current knowledge of the genetics of speciation.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.045 |
| Scholarly communication | 0.004 | 0.015 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".