Origins and Global Dissemination of Siluriformes A Phylogenetic Perspective on Historical Trajectories
Bibliographic record
Abstract
Catfishes (order Siluriformes ), arguably the most diverse and widely ranging freshwater fishes with a diversity of ecological niches on all but one continent, Antarctica. Their evolutionary origin and global dispersal are of particular importance for reconstructing freshwater biogeographic history and delineating lineage diversification patterns in aquatic habitats. Here, we build the phylogenetic framework of Siluriformes from mitochondrial and nuclear molecular information, date the divergence, and describe prevailing lineages with distinctive geographical signatures. By integrating fossil records, paleogeographic reconstructions, and modern biogeographic modeling approaches (such as DEC and BioGeoBEARS), this study proposes that South America may have been the evolutionary cradle of catfishes. It suggests that catfishes could have achieved transcontinental dispersal through ancient river connections, continental drift, and climatic fluctuations. In addition, the study explores regional adaptation and niche differentiation across various ecosystems, as well as the close interplay between local evolutionary responses and global expansion. This research provides a comprehensive perspective on the evolutionary history of catfishes and offers practical insights for freshwater biodiversity conservation and future biogeographic predictions.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".