{"id":"W4281708998","doi":"10.3390/jrfm15060246","title":"A New Look at the Swing Contract: From Linear Programming to Particle Swarm Optimization","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Swing; Particle swarm optimization; Computer science; Process (computing); Swarm intelligence; Futures contract; Operations research; Artificial intelligence; Risk analysis (engineering); Economics; Machine learning; Business; Financial economics; Engineering","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":[0.002147101,0.0009795276,0.001269268,0.0009557565,0.0005522241,0.00263021,0.001135419,0.002257253,0.003808819],"category_scores_gemma":[0.007951403,0.0005195774,0.0008414793,0.001524101,0.003120964,0.005000918,0.002069787,0.006420247,0.000483892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001050053,"about_ca_system_score_gemma":0.0008733648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002522638,"about_ca_topic_score_gemma":0.001360701,"domain_scores_codex":[0.999009,0.0005803915,0.00003958864,0.0001216805,0.0002115916,0.00003768291],"domain_scores_gemma":[0.9968975,0.002414851,0.0001921903,0.0001264005,0.0002628491,0.0001062161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004772168,0.00007716942,0.001011149,0.0003059544,0.0000719902,0.0001644594,0.0003021458,0.1569015,0.0004357967,0.7776653,0.009999774,0.05301719],"study_design_scores_gemma":[0.00001785572,0.00007974929,0.0003768425,0.0001636978,0.00001260911,0.00007545407,0.0001133555,0.3961248,0.000166051,0.5847156,0.0181193,0.00003476226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008046067,0.02066685,0.927251,0.02029269,0.001065472,0.00004289104,0.00009285499,0.00007876007,0.02246341],"genre_scores_gemma":[0.4529839,0.06097341,0.4382416,0.008518915,0.008652597,0.0003100189,0.0001979776,0.0003429271,0.02977857],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003808819,"threshold_uncertainty_score":0.0127418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01247823103077795,"score_gpt":0.2006969847550542,"score_spread":0.1882187537242762,"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."}}