{"id":"W2147187114","doi":"10.4028/www.scientific.net/amr.33-37.795","title":"An Intelligent Modeling Method Based on Genetic Programming and Genetic Algorithm","year":2008,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Association of Emergency Physicians","funders":"National Safety Academic Fund","keywords":"Crossover; Genetic programming; Fitness function; Computer science; Genetic algorithm; Algorithm; MATLAB; Parsing; Parse tree; Mathematical optimization; Data mining; Artificial intelligence; Machine learning; Mathematics; Programming language","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":[0.0004113062,0.0002296232,0.0003340046,0.000224554,0.0002403243,0.00008147561,0.0002069391,0.00009701701,0.0000309966],"category_scores_gemma":[0.00004197391,0.0002199528,0.00003091786,0.0002105291,0.00006433896,0.0001328057,0.00003233905,0.0002111558,0.00002708366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000914581,"about_ca_system_score_gemma":0.00002450287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004592629,"about_ca_topic_score_gemma":0.000003274477,"domain_scores_codex":[0.9977172,0.0002888322,0.000381054,0.0004353033,0.0004910029,0.0006865886],"domain_scores_gemma":[0.999001,0.000139322,0.00002402434,0.0004711068,0.0001484352,0.0002160835],"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":[0.00003683918,0.00002234855,0.000008268104,0.00005563471,0.000008063663,0.00006206481,0.0001044135,0.6047658,0.2248407,0.00001241419,0.000001733997,0.1700817],"study_design_scores_gemma":[0.0004577866,0.0002580172,0.0000930277,0.00005099415,0.000004331625,0.0000468312,0.000105558,0.8999156,0.09800261,0.0003072789,0.0005183497,0.0002395918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3907834,0.0005002369,0.6077127,0.000008975595,0.0001752249,0.0005331007,0.00001278747,0.0002019972,0.00007152548],"genre_scores_gemma":[0.7138358,0.0003315103,0.2854069,0.00001263729,0.0001525664,0.0001605251,0.000008568309,0.00006942012,0.00002194976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3230525,"threshold_uncertainty_score":0.8969414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0506570872647038,"score_gpt":0.3563161610443745,"score_spread":0.3056590737796707,"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."}}