{"id":"W2065715262","doi":"10.1007/s11047-013-9368-7","title":"Generation of classification trees from variable weighted features","year":2013,"lang":"en","type":"article","venue":"Natural Computing","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Fundação para a Ciência e a Tecnologia","keywords":"Phylogenetic tree; Trait; Constraint (computer-aided design); Tree (set theory); Consistency (knowledge bases); Computer science; Theory of computation; Family tree; Artificial intelligence; Machine learning; Theoretical computer science; Biology; Mathematics; Combinatorics; Algorithm; Genetics; Gene","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":[0.0001013421,0.00008494516,0.0001081026,0.00005204632,0.000136745,0.0001745162,0.0005074826,0.00005272384,0.00001427049],"category_scores_gemma":[0.00002942001,0.00007234881,0.00002686681,0.0003407545,0.00001955165,0.0004292676,0.000133248,0.0001366693,0.00002749638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002073484,"about_ca_system_score_gemma":0.00002468378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005155662,"about_ca_topic_score_gemma":0.000007389838,"domain_scores_codex":[0.9991825,0.0000343686,0.0002087841,0.0002756377,0.0001659997,0.0001327112],"domain_scores_gemma":[0.9991868,0.0001110195,0.0001449222,0.0003645519,0.0001582926,0.00003447237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.111599e-7,0.00005092161,0.0003291113,0.000004883851,0.00002316394,2.488531e-7,0.0003977037,0.000122769,0.2549442,0.07083569,0.01243267,0.6608579],"study_design_scores_gemma":[0.0001011808,0.00001091939,0.03959621,0.00001416594,0.000003691079,0.000001511291,0.00002032874,0.9497842,0.007995626,0.001799382,0.0005816422,0.00009116162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3027301,0.0003791715,0.6943437,0.0008136738,0.0004738877,0.0001906998,0.00001094978,0.0001779485,0.0008799085],"genre_scores_gemma":[0.6214295,0.000001824499,0.3781925,0.00007131349,0.0001486965,0.000004183821,0.00008303341,0.000003080097,0.00006581853],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9496614,"threshold_uncertainty_score":0.2950299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03415689047719922,"score_gpt":0.2655480904786237,"score_spread":0.2313912000014245,"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."}}