{"id":"W2007492229","doi":"10.1089/106652704773416966","title":"From a Phylogenetic Tree to a Reticulated Network","year":2004,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Reticulate; Reticulate evolution; Phylogenetic tree; Phylogenetic network; Biology; Phylogenetics; Evolutionary biology; Tree (set theory); Most recent common ancestor; Ancestor; Paleontology; Genetics; Gene; Combinatorics; Mathematics; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0001317868,0.0001170188,0.0002060279,0.00004915597,0.00005109148,0.00000937019,0.0001768693,0.00009380401,0.000008560215],"category_scores_gemma":[0.00006127752,0.0001000662,0.0001102848,0.00009621347,0.00005614043,4.87224e-7,0.00007861703,0.00006803266,0.00001031976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001809487,"about_ca_system_score_gemma":0.000130918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001340186,"about_ca_topic_score_gemma":0.00001402018,"domain_scores_codex":[0.9991722,0.00005109745,0.0003508422,0.000166874,0.00008307948,0.0001759014],"domain_scores_gemma":[0.9993365,0.0000366541,0.000183251,0.000101117,0.0002451765,0.00009727849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002682744,0.00007269174,0.00647812,0.000002084892,0.0003667359,0.00001059314,0.00015693,0.5446119,0.4420863,0.000684763,0.001479066,0.003782553],"study_design_scores_gemma":[0.006542938,0.00692771,0.4726969,0.00009023278,0.0001906681,0.0004233232,0.0001436078,0.0002712599,0.0393135,0.3976735,0.07483838,0.0008880064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741224,0.001650645,0.02263905,0.0009857918,0.0003754696,0.00007727392,0.00001921995,0.000001354886,0.0001287958],"genre_scores_gemma":[0.9625935,0.00005634651,0.03533367,0.0008514296,0.001110787,0.000002390143,0.0000308858,0.00001053802,0.00001042834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5443406,"threshold_uncertainty_score":0.4080581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009135419365097668,"score_gpt":0.2517320367021659,"score_spread":0.2425966173370682,"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."}}