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Record W7135065968 · doi:10.5376/ijmec.2025.15.0006

Phylogenetic Reconstruction and Genomic Adaptive Evolution in Siniperca spp.

2025· article· W7135065968 on OpenAlexvenueno aff
Chengmin Sun, Rudi Mai

Bibliographic record

VenueInternational Journal of Molecular Ecology and Conservation · 2025
Typearticle
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhylogenetic treeAdaptation (eye)PhylogeneticsDivergence (linguistics)Molecular clockAdaptive evolutionCladeGenomicsAdaptive value

Abstract

fetched live from OpenAlex

Siniperca or Chinese perch is a freshwater fish family indigenous to East Asia, of great economic value and ecological particularity. Though of great significance in aquaculture, the phylogenetic histories of the Siniperca genus are unclear due to morphological convergence and a dearth of molecular data. We rebuilt the genome-wide single-copy orthologous genes-based phylogenetic framework of Siniperca and inferred divergence times between species using a molecular clock model in this study. We further performed comparative genomics to identify expansions of gene families, positive selection signals, and adaptive evolutionary trajectories linked with ecological specialization. Several genetic candidates for environmental tolerance, immune response, and sensory systems were detected, suggesting lineage-specific adaptation to various freshwater environments. This study not only illuminates the phylogenetic history of Siniperca , but also reveals the genetic mechanism of its adaptive divergence, providing theoretical evidence for species conservation, utilization of resources, and molecular breeding in aquaculture.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.230
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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