Higher level molecular phylogeny of darkling beetles ( <scp>C</scp> oleoptera: <scp>T</scp> enebrionidae)
Bibliographic record
Abstract
Abstract Insect diversity represents about 60% of the estimated million‐and‐a‐half described eukaryotic species worldwide, yet comprehensive and well‐resolved intra‐ordinal phylogenies are still lacking for the majority of insect groups. This is the case especially for the most species‐rich insect group, the beetles ( C oleoptera), a group for which less than 4% of the known species have had their DNA sequenced. In this study, we reconstruct the first higher level phylogeny based on DNA sequence data for the species‐rich darkling beetles, a family comprising at least 20 000 species. Although amongst all families of beetles T enebrionidae ranks seventh in terms of species diversity, the lack of knowledge on the phylogeny and systematics of the group is such that its monophyly has been questioned (not to mention those of the subfamilies and tribes contained within it). We investigate the evolutionary history of T enebrionidae using multiple phylogenetic inference methods ( B ayesian inference, maximum likelihood and parsimony) to analyse a dataset consisting of eight gene fragments across 404 taxa (including 250 tenebrionid species). Although the resulting phylogenetic framework only encompasses a fraction of the known tenebrionid diversity, it provides important information on their systematics and evolution. Whatever the methods used, our results provide strong support for the monophyly of the family, and highlight the likely paraphyletic or polyphyletic nature of several important tenebrionid subfamilies and tribes, notably the polyphyletic subfamilies D iaperinae and T enebrioninae that clearly require substantial revision in the future. Some interesting associations in several groups are also revealed by the phylogenetic analyses, such as the pairing of Aphtora Bates with P hrenapatinae. Furthermore this study advances our knowledge of the evolution of the group, providing novel insights into much‐debated theories, such as the apparent relict distribution of the tribe E lenophorini.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".