{"id":"W2011993410","doi":"10.1016/j.ast.2014.04.004","title":"Low-thrust trajectory design with constrained particle swarm optimization","year":2014,"lang":"en","type":"article","venue":"Aerospace Science and Technology","topic":"Spacecraft Dynamics and Control","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Particle swarm optimization; Thrust; Trajectory; Trajectory optimization; Multi-swarm optimization; Particle (ecology); Control theory (sociology); Aerospace engineering; Mathematical optimization; Computer science; Physics; Engineering; Mathematics; Geology; Artificial intelligence","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":[0.0002276518,0.00009791061,0.0001117993,0.0001154625,0.00013176,0.00004831918,0.0001506611,0.00007252178,0.000007902914],"category_scores_gemma":[0.00005707336,0.00008244535,0.000006719727,0.0007633746,0.0007583291,0.0001408042,0.00002002925,0.00009478243,0.000005012499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002955082,"about_ca_system_score_gemma":0.00004635792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002791764,"about_ca_topic_score_gemma":0.00001331379,"domain_scores_codex":[0.9992926,0.000006288407,0.00007216178,0.0002000068,0.0001318321,0.0002970794],"domain_scores_gemma":[0.9996215,0.00002508189,0.00001867534,0.0001865329,0.00008453172,0.00006373507],"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":[0.00002069955,0.00004845701,0.002836369,0.00002558961,0.00002758213,0.000008534161,0.0002557494,0.4796564,0.4475089,0.03233404,0.0001099858,0.03716771],"study_design_scores_gemma":[0.0004339705,0.0001606325,0.0001451401,0.000009657699,0.000007537708,0.00001568377,0.0001908092,0.9577766,0.04086033,0.0002099384,0.000059358,0.0001303632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3112445,0.00008461483,0.6862364,0.001064725,0.00006788781,0.0001579083,5.828627e-7,0.0004521146,0.0006912882],"genre_scores_gemma":[0.9901081,0.00002995338,0.009744843,0.00005099416,0.00000901971,0.00002259566,2.558983e-7,0.00001101025,0.00002325772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6788636,"threshold_uncertainty_score":0.3362024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003271104028031969,"score_gpt":0.1684758946865334,"score_spread":0.1652047906585014,"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."}}