{"id":"W2913529671","doi":"10.1109/ssci.2018.8628863","title":"Hybrid Metaheuristic Algorithm for Clustering","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Metaheuristic; Cluster analysis; Tabu search; Computer science; Parallel metaheuristic; Heuristics; Artificial intelligence; Data mining; Machine learning; Meta-optimization","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":[0.0003362242,0.0001366216,0.0001571683,0.0001174515,0.0002227675,0.0001798807,0.001058817,0.00002585832,0.0000367712],"category_scores_gemma":[0.0001033868,0.0001225418,0.00006523721,0.000207215,0.00009411544,0.0004335539,0.000665834,0.0000862962,0.0001941922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005835666,"about_ca_system_score_gemma":0.00004760855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001377941,"about_ca_topic_score_gemma":0.000003778532,"domain_scores_codex":[0.9984873,0.0000284197,0.0001952893,0.0004833813,0.0002849281,0.0005207025],"domain_scores_gemma":[0.9987324,0.0001804798,0.00004069379,0.0006455997,0.0002595555,0.0001412889],"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":[0.000003032876,0.0000192685,0.000001065468,0.00001014302,0.00001598301,0.00001021242,0.00005584496,0.00004763851,0.0003398283,0.00195019,0.001039472,0.9965073],"study_design_scores_gemma":[0.0003201737,0.0002188347,0.00001960318,0.000006834984,0.00000253149,0.00005229954,0.000005846816,0.9629037,0.01073134,0.005894582,0.01967734,0.000166847],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009808975,0.0000295029,0.9959164,0.0003152557,0.0005807091,0.0002801103,0.00000529324,0.0003650787,0.002409616],"genre_scores_gemma":[0.01485854,0.000003746251,0.9801895,0.0002475865,0.0003999638,0.00007081462,0.000001749527,0.00001945221,0.004208662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9963405,"threshold_uncertainty_score":0.4997108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03140047396787493,"score_gpt":0.3250039390918261,"score_spread":0.2936034651239512,"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."}}