{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003906649,0.0004310251,0.001201861,0.001499162,0.001173994,0.001403537,0.00177311,0.001402631,0.001779845],"category_scores_gemma":[0.01895287,0.000599481,0.001276833,0.002285021,0.00228761,0.004839807,0.001433538,0.001534703,0.000215499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001410009,"about_ca_system_score_gemma":0.0006010953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001589859,"about_ca_topic_score_gemma":0.002562963,"domain_scores_codex":[0.9987057,0.0004267357,0.00009030248,0.000497676,0.0001774862,0.0001020311],"domain_scores_gemma":[0.9883136,0.008722304,0.001395493,0.0009661168,0.0002839874,0.0003184903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001254307,0.0002505176,0.2076209,0.0007666069,0.0003869343,0.0009952011,0.00182197,0.5245085,0.0147862,0.1149006,0.004726722,0.1279816],"study_design_scores_gemma":[0.0001440421,0.0001331621,0.01865213,0.0000416492,0.0001053698,0.001535994,0.0003939506,0.7591922,0.00368999,0.2125451,0.003521272,0.00004510392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8444986,0.0009201063,0.1512087,0.001073905,0.00001826582,0.00006871927,0.000510585,0.0001937676,0.00150744],"genre_scores_gemma":[0.906404,0.0003857311,0.09111402,0.0001688559,0.00003403757,0.00008685666,0.000896989,0.00008660124,0.0008229534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003906649,"threshold_uncertainty_score":0.02066058,"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."}}