{"id":"W1975585879","doi":"10.1080/09540091.2014.948385","title":"Global–local population memetic algorithm for solving the forward kinematics of parallel manipulators","year":2014,"lang":"en","type":"article","venue":"Connection Science","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Memetic algorithm; Crossover; Computer science; Population; Evolutionary algorithm; Local search (optimization); Kinematics; Evolutionary computation; Genetic algorithm; Computation; Mathematical optimization; Algorithm; Artificial intelligence; Mathematics; Machine learning","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":[0.0006089971,0.00007325427,0.0001092066,0.00004859665,0.0001587366,0.00003771163,0.0001793824,0.0000337688,0.000005646034],"category_scores_gemma":[0.0001564283,0.00005562142,0.000042207,0.0003640202,0.00007810493,0.0001316495,0.00002310848,0.00002997588,0.000002000473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007186688,"about_ca_system_score_gemma":0.00001180936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002550534,"about_ca_topic_score_gemma":0.00001996491,"domain_scores_codex":[0.9992741,0.000007406227,0.0002079802,0.0001258028,0.0002177619,0.0001669138],"domain_scores_gemma":[0.9995419,0.00008166636,0.0000553656,0.0001889041,0.00008816706,0.00004399539],"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":[5.980745e-7,0.000003367041,0.00008088403,0.00002212556,0.000002959027,2.376034e-8,0.00003324138,0.8776839,0.0002205198,0.08381808,0.0000200938,0.03811416],"study_design_scores_gemma":[0.000107402,0.00003048755,0.001734288,0.00001252959,0.00001117349,0.000003801094,0.00009633265,0.977519,0.000162625,0.02022575,0.00002859118,0.00006803454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01441439,0.00001207757,0.9842629,0.00003075346,0.0007578346,0.0001760457,0.00000194766,0.00006434129,0.000279638],"genre_scores_gemma":[0.7962902,0.000002673037,0.2036224,0.00002075022,0.00003597183,0.00001078509,0.000001688383,0.000005917412,0.000009652714],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7818758,"threshold_uncertainty_score":0.2268176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01274694218316518,"score_gpt":0.2453584346619545,"score_spread":0.2326114924787893,"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."}}