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Record W4292356922 · doi:10.1111/zsc.12559

The (non) accuracy of mitochondrial genomes for family‐level phylogenetics in Erebidae (Lepidoptera)

2022· article· en· W4292356922 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZoologica Scripta · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsCanadian Food Inspection Agency
FundersVetenskapsrådet
KeywordsErebidaeBiologyPhylogenetic treeMitochondrial DNAEvolutionary biologySubfamilyPhylogeneticsGenomeDNA sequencingSystematicsGeneticsLepidoptera genitaliaZoologyTaxonomy (biology)GeneEcology

Abstract

fetched live from OpenAlex

Abstract The use of molecular data to study the evolutionary history of organisms has revolutionized the field of systematics. Now with the appearance of high throughput sequencing (HTS) technologies, more and more genetic sequence data are available. One of the important sources of genetic data for phylogenetic analyses has been mitochondrial DNA. The limitations of mitochondrial DNA for the study of phylogenetic relationships have been thoroughly explored in the age of single locus phylogenetic studies. Now with the appearance of genomic scale data, increasing number of mitochondrial genomes are available, leading to an increasing number of mitophylogenomic studies. Here, we assemble 47 mitochondrial genomes using whole genome Illumina short reads from representatives of the family Erebidae (Lepidoptera), in order to evaluate the accuracy of mitochondrial genome application in resolving deep phylogenetic relationships. We find that mitogenomes are inadequate for resolving subfamily‐level relationships in Erebidae, but given good taxon sampling, we see its potential in resolving lower level phylogenetic relationships.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.572

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 science0.0010.000
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 head0.035
GPT teacher head0.258
Teacher spread0.223 · 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