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Record W4378172437 · doi:10.1093/gbe/evad092

Effect of Different Types of Sequence Data on Palaeognath Phylogeny

2023· article· en· W4378172437 on OpenAlexfundno aff
Naoko Takezaki

Bibliographic record

VenueGenome Biology and Evolution · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsnot available
FundersInstitute of GeneticsMinistry of Education, Culture, Sports, Science and Technology
KeywordsBiologyPhylogeneticsEvolutionary biologySequence (biology)Computational biologyGeneticsGene

Abstract

fetched live from OpenAlex

Palaeognathae consists of five groups of extant species: flighted tinamous (1) and four flightless groups: kiwi (2), cassowaries and emu (3), rheas (4), and ostriches (5). Molecular studies supported the groupings of extinct moas with tinamous and elephant birds with kiwi as well as ostriches as the group that diverged first among the five groups. However, phylogenetic relationships among the five groups are still controversial. Previous studies showed extensive heterogeneity in estimated gene tree topologies from conserved nonexonic elements, introns, and ultraconserved elements. Using the noncoding loci together with protein-coding loci, this study investigated the factors that affected gene tree estimation error and the relationships among the five groups. Using closely related ostrich rather than distantly related chicken as the outgroup, concatenated and gene tree-based approaches supported rheas as the group that diverged first among groups (1)-(4). Whereas gene tree estimation error increased using loci with low sequence divergence and short length, topological bias in estimated trees occurred using loci with high sequence divergence and/or nucleotide composition bias and heterogeneity, which more occurred in trees estimated from coding loci than noncoding loci. Regarding the relationships of (1)-(4), the site patterns by parsimony criterion appeared less susceptible to the bias than tree construction assuming stationary time-homogeneous model and suggested the clustering of kiwi and cassowaries and emu the most likely with ∼40% support rather than the clustering of kiwi and rheas and that of kiwi and tinamous with 30% support each.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.286
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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