{"id":"W4250763014","doi":"10.1177/117693430800400003","title":"Why Should We Care about Molecular Coevolution?","year":2008,"lang":"en","type":"article","venue":"Evolutionary Bioinformatics","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Genetics","funders":"Science Foundation Ireland","keywords":"Coevolution; Computer science; Parametric statistics; Independence (probability theory); Phylogenetic tree; Computational biology; Amino acid; Amino acid residue; Data science; Biology; Evolutionary biology; Mathematics; Peptide sequence; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008630457,0.0003000771,0.000201633,0.0001229831,0.000450067,0.00001775898,0.0003479807,0.0003055463,0.00007637717],"category_scores_gemma":[0.00007195715,0.0003073453,0.0002077013,0.0002472433,0.0003333814,0.00002083912,0.0002094503,0.0001823147,0.0001803067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001032788,"about_ca_system_score_gemma":0.0002862401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000183933,"about_ca_topic_score_gemma":0.00002097906,"domain_scores_codex":[0.9982766,0.00005232934,0.0004980927,0.0002906879,0.0004266653,0.0004556222],"domain_scores_gemma":[0.9987115,0.00001003494,0.0001450872,0.0006239152,0.0003051106,0.0002043846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002366474,0.0004260368,0.01566656,0.0004872939,0.0003517231,0.00007284124,0.003001212,0.04291803,0.0268145,0.004428677,0.9010639,0.004532592],"study_design_scores_gemma":[0.001858919,0.0006242024,0.02136116,0.00006875739,0.00006563749,0.0009518347,0.001677652,0.0551995,0.003465766,0.0003550274,0.9131526,0.001218965],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3789185,0.05080854,0.5006781,0.003919864,0.001924673,0.001754556,0.0007198476,0.0004996951,0.06077623],"genre_scores_gemma":[0.9158124,0.004623935,0.06831024,0.005437497,0.000403025,0.00006805568,0.002444403,0.00007802862,0.002822421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5368938,"threshold_uncertainty_score":0.9999379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0114456397480938,"score_gpt":0.2425636756196013,"score_spread":0.2311180358715076,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}