Phylogenetic relationships and systematics of the genus Tetranychus: A morphological and molecular approach
Bibliographic record
Abstract
AbstractThe genus Tetranychus (Acari: Tetranychidae), commonly known as spider mites, includes many agriculturally significant species. Understanding the phylogenetic relationships within Tetranychus is critical for improving pest management strategies. This research work explores the evolutionary relationships of the genus using both morphological and molecular approaches. The introduction highlights the significance of Tetranychus as pests and the need for precise taxonomic frameworks. We also discuss the limitations of using either morphological or molecular data in isolation. Through the results, we reveal phylogenetic relationships based on analyses of mitochondrial genes like cytochrome oxidase I (COI) and ribosomal sequences, correlating these findings with morphological traits such as body setation and sensory structures. Our findings indicate that while morphological characteristics offer key diagnostic features, molecular data provide more robust support for phylogenetic groupings within Tetranychus. This integrated approach not only improves species delimitation but also helps resolve taxonomic ambiguities. Combining morphological and molecular methods enhances our understanding of Tetranychus systematics. This dual approach provides insights into the evolutionary history of the genus, enabling more accurate classifications and contributing to effective pest control strategies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".