{"id":"W2133130908","doi":"10.1093/molbev/msl155","title":"Testing for Covarion-like Evolution in Protein Sequences","year":2006,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Canadian Institute for Advanced Research","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada; Canadian Institutes of Health Research; Genome Atlantic; Canadian Institute for Advanced Research; Alfred P. Sloan Foundation","keywords":"Tree (set theory); Biology; Phylogenetic tree; Variable (mathematics); Markov chain; Markov model; Process (computing); Protein evolution; Substitution (logic); Biological system; Rate of evolution; Computer science; Mathematics; Statistics; Genetics; Combinatorics; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001930951,0.0001206452,0.0001136495,0.00005412256,0.0001121698,0.000007974504,0.00006290012,0.0001722003,5.017263e-7],"category_scores_gemma":[0.00007591387,0.0001189884,0.00003712385,0.00008834663,0.0001200969,0.000001037424,0.00005253878,0.00004548876,9.299296e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002955542,"about_ca_system_score_gemma":0.00005125044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000433588,"about_ca_topic_score_gemma":0.0002277068,"domain_scores_codex":[0.9991875,0.00005556496,0.0001719153,0.0003232045,0.00003026001,0.0002315157],"domain_scores_gemma":[0.9997259,0.00001222511,0.00005953411,0.00011213,0.00006877237,0.00002148041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003797531,0.00002166128,0.08033375,0.00001132259,0.00001162622,7.055665e-7,0.000004383626,0.0002267488,0.910365,0.008639299,0.00002990919,0.0003175646],"study_design_scores_gemma":[0.001807842,0.001338646,0.7607175,0.0000418934,0.00003841103,0.0000364248,0.00007735915,0.001228353,0.1068406,0.1233711,0.003896208,0.0006057006],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9507892,0.004024012,0.04438149,0.0001002252,0.00008611177,0.0003555496,0.00001711296,0.000005063216,0.0002412252],"genre_scores_gemma":[0.9939027,0.00000806611,0.005675896,0.00004470819,0.00009977924,0.000119568,0.00007332647,0.000009293644,0.00006659737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8035244,"threshold_uncertainty_score":0.4852207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00897576358867822,"score_gpt":0.2416655305473518,"score_spread":0.2326897669586736,"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."}}