{"id":"W1488609668","doi":"10.1109/cec.2005.1554756","title":"Making soccer kicks better: A Study in Particle Swarm Optimization and Evolution Strategies","year":2005,"lang":"en","type":"article","venue":"","topic":"Educational Games and Gamification","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Particle swarm optimization; Biomechanics; Computer science; Sports biomechanics; Swarm behaviour; Simulation; Multi-swarm optimization; Artificial intelligence; Machine learning; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002604033,0.0007461673,0.0007890701,0.0007045631,0.0004709831,0.001084415,0.0005404885,0.001390242,0.0009603542],"category_scores_gemma":[0.01264352,0.000281154,0.0005675621,0.0007000974,0.001274485,0.001595771,0.000445328,0.001100543,0.0001081118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007366872,"about_ca_system_score_gemma":0.0006121008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00567821,"about_ca_topic_score_gemma":0.002124214,"domain_scores_codex":[0.9990263,0.000604495,0.00003269197,0.00008517363,0.000179409,0.00007193986],"domain_scores_gemma":[0.9942713,0.004945336,0.000220485,0.0001341359,0.0003403677,0.00008833874],"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":[0.0001543584,0.0005035835,0.00762431,0.0002560583,0.0002743263,0.0002198538,0.001347231,0.6705291,0.002117963,0.2393894,0.002169492,0.07541427],"study_design_scores_gemma":[0.00006754293,0.0001792073,0.002334309,0.00003105202,0.00002523017,0.00003424616,0.0002547787,0.9642987,0.0003545317,0.03040377,0.002000701,0.00001585196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6171161,0.005816646,0.3252476,0.00569734,0.00021915,0.0003008996,0.00005309608,0.0001042797,0.04544493],"genre_scores_gemma":[0.9362187,0.002222752,0.05745737,0.0002663485,0.0001133859,0.0001542063,0.00003116263,0.00004420667,0.00349181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00567821,"threshold_uncertainty_score":0.01377165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0496418323721033,"score_gpt":0.376597961892129,"score_spread":0.3269561295200257,"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."}}