{"id":"W2034206612","doi":"10.1089/cmb.2008.0054","title":"Gene Family Evolution by Duplication, Speciation, and Loss","year":2008,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal; Université de Montréal; Simon Fraser University; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University","keywords":"Gene duplication; Genetic algorithm; Gene family; Biology; Tree rearrangement; Gene; Heuristic; Tree (set theory); Evolutionary biology; Phylogenetics; Computational biology; Genetics; Computer science; Mathematics; Genome; Combinatorics; Artificial intelligence","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":[0.0001139784,0.0000720547,0.0001165214,0.00004107844,0.00008952752,0.000004001379,0.00007469138,0.00006580543,0.00000223988],"category_scores_gemma":[0.00003847468,0.00006450281,0.00004198205,0.00004281421,0.0001173436,0.000001231553,0.00003240409,0.00004325335,0.000002041347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001408727,"about_ca_system_score_gemma":0.00008302218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000367685,"about_ca_topic_score_gemma":6.296301e-7,"domain_scores_codex":[0.9994416,0.00003768758,0.0002601303,0.0001123677,0.00006410165,0.00008407445],"domain_scores_gemma":[0.9993314,0.00002673179,0.0002101758,0.00005416264,0.0003346962,0.00004280616],"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":[0.00008734458,0.00007026512,0.127522,0.000003590786,0.0001603429,0.000002413806,0.00006829528,0.002560701,0.8568807,0.001260622,0.01034419,0.001039581],"study_design_scores_gemma":[0.001253549,0.0007601983,0.9156926,0.000003869118,0.00002513919,0.000757715,0.00003532663,0.0001634787,0.01499586,0.01943143,0.04666987,0.0002109597],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694392,0.005786136,0.0240845,0.000416248,0.0001250096,0.00004079409,0.0000231438,8.506643e-7,0.00008412822],"genre_scores_gemma":[0.9940524,0.00105426,0.004240787,0.0002446013,0.0003118351,0.000001438617,0.00004488598,0.0000052493,0.00004454551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8418848,"threshold_uncertainty_score":0.2630348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008717990535582093,"score_gpt":0.2306207468131898,"score_spread":0.2219027562776077,"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."}}