{"id":"W2945531413","doi":"10.1109/tsmc.2019.2906635","title":"Fuzzy Grey Choquet Integral for Evaluation of Multicriteria Decision Making Problems With Interactive and Qualitative Indices","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Choquet integral; Fuzzy logic; Multiple-criteria decision analysis; Consistency (knowledge bases); Mathematics; Preference; Ideal solution; Computer science; Fuzzy number; Mathematical optimization; Data mining; Artificial intelligence; Machine learning; Fuzzy set; Statistics","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":[0.004211651,0.001336734,0.001152253,0.001964113,0.0007439537,0.001551407,0.00102589,0.0009746161,0.00108444],"category_scores_gemma":[0.006630301,0.0003473212,0.001174735,0.001710098,0.001029623,0.001543037,0.001303528,0.001146409,0.0001520298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484679,"about_ca_system_score_gemma":0.001890955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0056016,"about_ca_topic_score_gemma":0.003707586,"domain_scores_codex":[0.9971402,0.001191624,0.0001282212,0.0002502434,0.001165556,0.0001242356],"domain_scores_gemma":[0.9988571,0.0006322851,0.00009188869,0.00004726769,0.0003335005,0.00003782833],"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":[0.0001097628,0.00006146553,0.001064643,0.000361896,0.000179811,0.0001403239,0.0003377443,0.8303678,0.007641961,0.06024256,0.000824951,0.09866703],"study_design_scores_gemma":[0.0000058634,0.00002203182,0.0001380031,0.00001336874,0.00001674722,0.00001469884,0.0000183221,0.9920322,0.0006784375,0.006578684,0.0004694179,0.00001226566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008056561,0.0004709014,0.9892805,0.00005652155,0.00002582725,0.00003250716,0.000008370086,0.00006146543,0.00200734],"genre_scores_gemma":[0.6249145,0.0009927398,0.3721534,0.00006381745,0.00005321789,0.0002177689,0.00007339426,0.00006023703,0.00147085],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0056016,"threshold_uncertainty_score":0.0222736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1169925041019587,"score_gpt":0.4266774768565975,"score_spread":0.3096849727546389,"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."}}