ArticleSystematic biology2026
Comparing Partition and Mixture Models with Akaike Information Criteria.
Article in Systematic biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Phylogenomic mixture models outperform homogeneous and partitioned models.Molecular biology and evolution · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Sophisticated phylogenetic models often include mixture and/or partition model components. It was recently noted that information criteria tend to favour partition models over mixture models even in some cases where the latter are misspecified and give poor topological estimation. We show that this problem arises because partition models and mixture models fundamentally differ in their probability calculations: mixture models calculate likelihood contributions from sites as the marginal probability of the data averaging over parameter vectors that might have arisen at a site whereas partition model likelihood contributions are calculated as the probability of the site pattern conditional upon a fixed assigned parameter vector at that site. These differing probability calculations lead to AIC estimates that are not always comparable. We explore three generally applicable ways of correcting the issue.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.