A time and a place for everything: phylogenetic history and geography as joint predictors of oak plastome phylogeny
Bibliographic record
Abstract
Owing to high rates of introgressive hybridization, the plastid genome is poorly suited to fine-scale DNA barcoding and phylogenetic studies of the oak genus (Quercus, Fagaceae). At the tips of the oak plastome phylogeny, recent gene migration and reticulation generally cause topology to reflect geographic structure, while deeper branches reflect lineage divergence. In this study, we quantify the simple and partial effects of geographic proximity and nucleome-inferred phylogenetic history on oak plastome phylogeny at different evolutionary scales. Our study compares pairwise phylogenetic distances based on complete plastome sequences, pairwise phylogenetic distances from nuclear restriction site-associated DNA sequences (RADseq), and pairwise geographic distances for 34 individuals of the white oak clade representing 24 North American and Eurasian species. Within the North American white oak clade alone, phylogenetic history has essentially no effect on plastome variation, while geography explains 11%-21% of plastome phylogenetic variance. However, across multiple continents and clades, phylogeny predicts 30%-41% of plastome variation, geography 3%-41%. Tipwise attenuation of phylogenetic informativeness in the plastome means that in practical terms, plastome data has little use in solving phylogenetic questions, but can still be a useful barcoding or phylogenetic marker for resolving questions among major clades.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".