{"id":"W4392485970","doi":"10.18280/ijsse.140106","title":"Spurious Trip Rate Optimization Using Particle Swarm Optimization Algorithm","year":2024,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spurious relationship; Particle swarm optimization; Multi-swarm optimization; Algorithm; Computer science; Metaheuristic; Mathematical optimization; Optimization algorithm; Mathematics; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0006259466,0.001111319,0.001162568,0.0006351649,0.0004184786,0.0009813354,0.0006651176,0.001036447,0.001551665],"category_scores_gemma":[0.001106151,0.0005183897,0.0007811487,0.000632336,0.0004024169,0.0005305646,0.0006148454,0.0007676877,0.0002414755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004264105,"about_ca_system_score_gemma":0.001040206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00600297,"about_ca_topic_score_gemma":0.002895734,"domain_scores_codex":[0.9997209,0.00008717091,0.00002076866,0.0000556353,0.0000725646,0.00004294245],"domain_scores_gemma":[0.9996606,0.000171461,0.00005107719,0.00001563387,0.00008413819,0.00001698511],"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":[0.00002298903,0.00001690467,0.0003230186,0.00005675977,0.0000242764,0.00003222458,0.00001628488,0.988233,0.0005317272,0.001070518,0.000446178,0.009226109],"study_design_scores_gemma":[0.000006472532,0.00001807403,0.00008592676,0.000004324587,0.000005979786,0.000005088397,0.000005137063,0.9991426,0.0001285801,0.0003604723,0.0002349222,0.000002381654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02855555,0.0009039434,0.9634132,0.0002256124,0.0001155899,0.00009503898,0.00008412354,0.0002614209,0.006345602],"genre_scores_gemma":[0.7950149,0.0009809742,0.1963646,0.0001436916,0.00008394963,0.0004879085,0.0003264807,0.00008686777,0.006510664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00600297,"threshold_uncertainty_score":0.01193607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009628628730706114,"score_gpt":0.2496032963026306,"score_spread":0.2399746675719245,"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."}}