Mitochondrial Genome Variation in <i>Channa</i> and Its Implications for Phylogenetic Relationships
Bibliographic record
Abstract
The genus Channa is a kind of freshwater fish with important economic value and ecological significance. Its species diversity and phylogenetic relationship have long been concerned. This study systematically sorted and compared the mitochondrial genome sequences of different species and regional populations of the genus Channa , deeply revealed its genome structure composition, variation characteristics and phylogenetic relationship, clarified the lineage differentiation pattern and evolutionary path within the genus Channa , and constructed a high-resolution phylogenetic tree by analyzing genetic variations such as SNP, InDel and non-synonymous mutations. Regional comparison showed that there were significant differences in mitochondrial variation between the southern Chinese and Southeast Asian populations of Channa , and geographical isolation contributed to the formation of lineages in different regions. Case analysis represented by Channa argus and Channa maculata further revealed their genomic differences and ecological adaptation mechanisms. This study is expected to provide a theoretical basis for species identification, resource protection and genetic diversity assessment of Channa , and also provide a methodological reference and practical path for studying the phylogenetic relationship of freshwater fish using mitochondrial genome.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".