{"id":"W2075441601","doi":"10.1007/s10489-008-0137-8","title":"The property analysis of evolutionary algorithms applied to spanning tree problems","year":2008,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Computer science; Locality; Encoding (memory); Evolutionary algorithm; Tree (set theory); Property (philosophy); Spanning tree; Minimum spanning tree; Algorithm; Set (abstract data type); Population; Enhanced Data Rates for GSM Evolution; Theoretical computer science; Mathematical optimization; Artificial intelligence; Mathematics; Discrete mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003872609,0.0006626043,0.0009353725,0.001855808,0.0008483786,0.002226761,0.00137945,0.001294391,0.004114354],"category_scores_gemma":[0.02632016,0.0003991109,0.001586505,0.002247782,0.001614006,0.006394159,0.001089714,0.002191438,0.0005516273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008521646,"about_ca_system_score_gemma":0.0007209741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008008975,"about_ca_topic_score_gemma":0.0003078575,"domain_scores_codex":[0.9987658,0.0005745992,0.00006818373,0.0001174504,0.000357913,0.000116006],"domain_scores_gemma":[0.9868284,0.01048753,0.0006190452,0.0008320597,0.001057048,0.0001758259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001115352,0.0001056452,0.002178491,0.0002804096,0.00009360089,0.000217165,0.000251802,0.2129585,0.004760779,0.6949145,0.002960146,0.08116744],"study_design_scores_gemma":[0.00001000429,0.00005293838,0.000529404,0.00003340804,0.00003119878,0.000137575,0.00003401569,0.7876679,0.001167259,0.2088499,0.001475886,0.00001055961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04653316,0.001246118,0.938197,0.0006813551,0.00008396446,0.00005377447,0.00006947808,0.0001416163,0.01299358],"genre_scores_gemma":[0.8359869,0.002848523,0.1546384,0.0002138412,0.0004077996,0.0001565605,0.0002401456,0.0003342598,0.00517352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004114354,"threshold_uncertainty_score":0.02048051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05081212352583217,"score_gpt":0.2826052492951051,"score_spread":0.2317931257692729,"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."}}