{"id":"W2984747650","doi":"10.1016/j.asoc.2019.105930","title":"Estimating incomplete information in group decision making: A framework of granular computing","year":2019,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"King Abdulaziz University","keywords":"Granular computing; Granularity; Consistency (knowledge bases); Preference; Missing data; Fuzzy logic; Computer science; Complete information; Group decision-making; Data mining; Flexibility (engineering); Mathematics; Artificial intelligence; Machine learning; Rough set; Statistics; Mathematical economics; Social psychology","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":[0.01915879,0.002031497,0.005910836,0.005636871,0.001348042,0.009174741,0.003770547,0.003071006,0.001879835],"category_scores_gemma":[0.05428719,0.001418735,0.002950453,0.007533567,0.004860336,0.008684853,0.005157619,0.00397708,0.0001998133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003312753,"about_ca_system_score_gemma":0.002837983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00484114,"about_ca_topic_score_gemma":0.002625487,"domain_scores_codex":[0.9844235,0.009209938,0.001228547,0.001401298,0.002998702,0.0007379799],"domain_scores_gemma":[0.9605383,0.03163959,0.00296596,0.002516841,0.001629147,0.0007101993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001114951,0.0001007573,0.001254532,0.0004568956,0.0003814562,0.0002141692,0.0003815831,0.5648318,0.0004480995,0.3922032,0.0006636175,0.03895231],"study_design_scores_gemma":[0.00001842059,0.00002931506,0.0002191844,0.00009106015,0.00007066522,0.00002619023,0.00006909373,0.6491277,0.0002023281,0.3495656,0.0005505775,0.00002994512],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006882083,0.000665339,0.9903351,0.0006099941,0.00005096752,0.00006487872,0.00006270171,0.00004845125,0.001280431],"genre_scores_gemma":[0.4808027,0.001831683,0.5151324,0.0002256626,0.0003420205,0.0004189254,0.0001968485,0.00006156207,0.0009882582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01915879,"threshold_uncertainty_score":0.1013226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04415738569989185,"score_gpt":0.3668752219627582,"score_spread":0.3227178362628664,"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."}}