{"id":"W1583203589","doi":"10.3233/his-140198","title":"Recentering and restarting a genetic algorithm using a generative representation for an ordered gene problem1","year":2014,"lang":"en","type":"article","venue":"International Journal of Hybrid Intelligent Systems","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Brock University","funders":"Natural Sciences and Engineering Research Council of Canada; Brock University","keywords":"Generative grammar; Computer science; Representation (politics); Genetic algorithm; Artificial intelligence; Generative model; Algorithm; Theoretical computer science; Machine learning","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":[0.002120962,0.001001288,0.0008071839,0.0009944069,0.0008899655,0.001090632,0.002081744,0.002111673,0.001975395],"category_scores_gemma":[0.005071221,0.0004468096,0.001251054,0.001042694,0.001789162,0.001001793,0.001001323,0.001665132,0.0003208475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001208937,"about_ca_system_score_gemma":0.001043916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005918967,"about_ca_topic_score_gemma":0.006005272,"domain_scores_codex":[0.999315,0.0003206055,0.0000275289,0.00008757848,0.0001684814,0.00008078879],"domain_scores_gemma":[0.9975086,0.001720111,0.0001426684,0.0002965741,0.0002474618,0.00008451998],"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":[0.00006180338,0.0000774888,0.0006085125,0.00003127101,0.00002600453,0.000108423,0.0001363536,0.9317619,0.002594569,0.02402957,0.0005207622,0.04004326],"study_design_scores_gemma":[0.00001627318,0.00006055186,0.00008144919,0.000006233969,0.0000114306,0.00003226982,0.00001397864,0.9928589,0.001039564,0.005098395,0.0007703062,0.00001066324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1143711,0.0003550047,0.8757101,0.0003686405,0.0001025304,0.0001709107,0.00003825752,0.0005178793,0.008365524],"genre_scores_gemma":[0.5591102,0.0002541305,0.4345481,0.0001772612,0.00005027676,0.0001938243,0.0001354634,0.0001996421,0.005331137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005918967,"threshold_uncertainty_score":0.01176906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07319674962700776,"score_gpt":0.3568253381792253,"score_spread":0.2836285885522175,"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."}}