Is Cladogenesis Heritable?
Bibliographic record
Abstract
The heritability of speciation rates and extinction risks is a crucial parameter in models of macroevolution, but little direct evidence has been available to assess the occurrence, strength, or generality of this heritability. We tested for heritability using correlations between ancestral and descendent branch lengths in phylogenetic trees, an approach first applied to a bird phylogeny by Harvey et al. (1991, pages 123-137 in Genes in ecology [R. J. Berry et al., eds.], Blackwell Scientific, Oxford). We applied Harvey et al.'s test to some of the largest DNA sequence-based phylogenetic analyses published to date for plants, insects, fungi, and bacteria. If one of two parent lineages splits first and if this is the case for any heritable reason, then on average we expect its daughter lineages to also split first. We also used a randomization procedure to assess significance of branch length heritability. Using maximum parsimony and maximum likelihood branch lengths and trees made ultrametric after nonparametric rate smoothing or by enforcing a molecular clock, we found a pattern for most clades consistent with heritable net cladogenesis. Heritability of cladogenesis may be a general phenomenon, detectable across a large number of lineages and a broad range of taxa.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| 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".