Bibliographic record
Abstract
The likelihood of speciation in the face of homogenizing gene flow (i.e. without complete geographical isolation) is one of the most debated topics in evolutionary biology. Demonstrating this phenonemon is hampered by the difficulty of isolating the effects of time since population divergence vs. gene flow on levels of molecular genetic differentiation. For example, weak genetic differentiation between taxa could be due to recent divergence, gene flow, or a combination of these factors. Nonetheless, a number of convincing examples of speciation with gene flow have recently emerged, owing in part to the development of new analytical methods designed to estimate gene flow specifically. A recent example of speciation with gene flow in salamanders (Niemiller et al. 2008) further advances our understanding of this phenonemon, by showing that gene flow between cave and spring salamanders was ongoing during speciation, rather than having occurred after a long period of allopatric divergence. Future work on the ecological and genetic factors reducing gene flow will likely increase our understanding of the conditions that faciliate divergence in the face of gene flow.
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 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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.017 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".