{"id":"W4205441696","doi":"10.1145/1830761.1830913","title":"Statistical analysis for evolutionary computation","year":2010,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada; University of Guelph","funders":"","keywords":"Evolutionary computation; Citation; Computer science; Government (linguistics); Library science; Operations research; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01131107,0.002143271,0.002032993,0.004672228,0.001053723,0.003967187,0.002457116,0.002194303,0.0460196],"category_scores_gemma":[0.05323578,0.001393473,0.003204257,0.004745434,0.002398144,0.003907623,0.003044501,0.005548322,0.01823457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698693,"about_ca_system_score_gemma":0.003343728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001765693,"about_ca_topic_score_gemma":0.001838948,"domain_scores_codex":[0.9895374,0.006478672,0.0007119573,0.0009078464,0.00210519,0.0002591049],"domain_scores_gemma":[0.9697955,0.0213308,0.0009070951,0.003501116,0.004049191,0.0004162949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007420395,0.00007343393,0.001272835,0.001506507,0.0004218205,0.0002128465,0.0002438971,0.01537529,0.001379508,0.3817803,0.2045769,0.3930823],"study_design_scores_gemma":[0.00005109374,0.00006829604,0.001203081,0.0004921654,0.00008961296,0.0004015049,0.0000837999,0.0761865,0.0008710219,0.6586998,0.2617833,0.00006982261],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003364516,0.005066684,0.9811736,0.001842332,0.0008528327,0.0001340177,0.001004283,0.003408806,0.006180926],"genre_scores_gemma":[0.02536205,0.008672645,0.9387957,0.001923331,0.003101883,0.001971682,0.003840238,0.004349385,0.01198319],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0460196,"threshold_uncertainty_score":0.1539509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01369685416333222,"score_gpt":0.2860462464602212,"score_spread":0.272349392296889,"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."}}