The (non) accuracy of mitochondrial genomes for family‐level phylogenetics in Erebidae (Lepidoptera)
Bibliographic record
Abstract
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.
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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 | 0.002 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".