Pangenomes as a framework for adaptive radiation, speciation, and adaptation
Bibliographic record
Abstract
Understanding the genomic basis of diversification is a central goal in evolutionary biology. In recent years, the development and use of pangenomes, a genomic representation of multiple individuals within a lineage (a set of related populations, subspecies, ecotypes, or species), has enabled researchers to differentiate between DNA sequences shared by all individuals of a given lineage (core regions) from those present only in some individuals (accessory or variable regions). Differentiating between core and accessory regions has highlighted a key limitation of relying on a single reference genome: It captures the genetic code of only one individual and this biases genomic analyses and our understanding of diversification. Here, we propose that by identifying genes associated with both core and accessory regions, we can deepen our understanding of the processes underlying diversification. We suggest that analyzing pangenomes and accessory regions will provide deeper insights into diversification, hybridization, and the genetic basis of adaptation and speciation.
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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".