{"id":"W4298396118","doi":"10.1007/s00500-022-07498-7","title":"A comprehensive study on effect of multi-subgroup background in group decision-making","year":2022,"lang":"en","type":"article","venue":"Soft Computing","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Cluster analysis; Data mining; Particle swarm optimization; Computer science; Granularity; Set (abstract data type); Machine learning","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":[0.0109077,0.0005265255,0.001435372,0.0007070922,0.000735902,0.001268702,0.0006033565,0.0006457517,0.003460224],"category_scores_gemma":[0.03217703,0.0001446044,0.001817708,0.00115548,0.0005397605,0.001379336,0.0008773563,0.001020221,0.0002136735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040336,"about_ca_system_score_gemma":0.00220039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002667547,"about_ca_topic_score_gemma":0.002831093,"domain_scores_codex":[0.9924868,0.005679063,0.0002513551,0.000450369,0.0008786038,0.0002537686],"domain_scores_gemma":[0.9395304,0.05443984,0.001254789,0.001790551,0.00198577,0.0009986998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02699479,0.01126543,0.1046416,0.006894453,0.007501686,0.0002605298,0.003884654,0.04599744,0.009093569,0.01819846,0.002217651,0.7630497],"study_design_scores_gemma":[0.003732438,0.07431114,0.4374065,0.003777143,0.03182266,0.0006427444,0.01092733,0.293961,0.03163026,0.08735283,0.02391014,0.0005257324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658138,0.005453143,0.02297088,0.0005567212,0.0001233726,0.0003727478,0.0001523912,0.00004579277,0.00451109],"genre_scores_gemma":[0.9844469,0.001067545,0.01336356,0.0001663999,0.00004683425,0.0001459085,0.0000940244,0.00001736509,0.0006514955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0109077,"threshold_uncertainty_score":0.05768609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1401565352299772,"score_gpt":0.4496721565176673,"score_spread":0.3095156212876901,"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."}}