{"id":"W4386802716","doi":"10.23977/jnca.2023.080101","title":"Research on Large-scale Multi-target Units Combination Model Based on IAFSA","year":2023,"lang":"en","type":"article","venue":"Journal of Network Computing and Applications","topic":"Electric Power System Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Swarm behaviour; Weighting; Convergence (economics); Mathematical optimization; Computer science; Scale (ratio); Energy (signal processing); Algorithm; Rate of convergence; Mathematics; Key (lock); Statistics","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":[0.0007330564,0.0009861647,0.00115626,0.0004966593,0.0005558372,0.001284484,0.001686646,0.001040857,0.003004391],"category_scores_gemma":[0.0009377412,0.0005435963,0.001271094,0.0007920178,0.0006437509,0.001530599,0.0008992665,0.001112214,0.0002735145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009042236,"about_ca_system_score_gemma":0.001281687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01766039,"about_ca_topic_score_gemma":0.00836705,"domain_scores_codex":[0.9996507,0.00008843702,0.00001834501,0.00009572103,0.00009942956,0.00004736221],"domain_scores_gemma":[0.9996455,0.0001553449,0.00005109776,0.00001497536,0.0001036714,0.00002941355],"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":[0.00001052518,0.000007664237,0.000248984,0.00002746737,0.00002078091,0.00003296462,0.00001574738,0.9931158,0.0003345321,0.001983723,0.0001955388,0.004006253],"study_design_scores_gemma":[0.000002091542,0.000007464138,0.00004272334,0.000001448066,0.000003637519,0.000004192088,0.000003996908,0.9992691,0.00003805195,0.0005094021,0.0001161187,0.000001727283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03244659,0.0005682482,0.9580553,0.0002650773,0.00007949937,0.00007937891,0.00007454897,0.0001771253,0.008254247],"genre_scores_gemma":[0.9213352,0.0006821704,0.06791702,0.00008715757,0.00005985609,0.0003266848,0.0001901544,0.00006809533,0.009333595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01766039,"threshold_uncertainty_score":0.03511518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03902825999438042,"score_gpt":0.3138163660665046,"score_spread":0.2747881060721242,"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."}}