{"id":"W4403583470","doi":"10.1016/j.asoc.2024.112362","title":"Synthesizing complexity: Trends, challenges, and future directions in fuzzy-based multicriteria decision-making (FMCDM) methods","year":2024,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Fuzzy logic; Management science; Operations research; Artificial intelligence; Mathematics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01041444,0.0005642188,0.001010857,0.002399254,0.0006006269,0.00155826,0.0009960482,0.0002966108,0.0003108608],"category_scores_gemma":[0.002566685,0.0004894615,0.0002354598,0.002414228,0.0002235915,0.0003357417,0.0007833442,0.0007407287,0.0001323013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001721303,"about_ca_system_score_gemma":0.00009701721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001719449,"about_ca_topic_score_gemma":0.0001011442,"domain_scores_codex":[0.9932151,0.0008147964,0.00176761,0.002003048,0.00137657,0.0008228265],"domain_scores_gemma":[0.9713117,0.02694337,0.000306478,0.001049522,0.0001673011,0.0002216592],"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":[0.00005723329,0.00005776807,0.00006983637,0.00004052609,0.0000231818,0.0000670779,0.003585873,0.0005614865,0.001038409,0.009731422,0.000174428,0.9845927],"study_design_scores_gemma":[0.0008324263,0.0000343767,0.01446081,0.001159225,0.00004499676,0.0000884307,0.004668809,0.7161515,0.0001288445,0.08971421,0.1717573,0.0009590113],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1100544,0.04164308,0.8186285,0.003283516,0.006935863,0.0009236324,0.00004274681,0.001533848,0.01695442],"genre_scores_gemma":[0.5795428,0.00008784574,0.4195678,0.0002185686,0.0004901963,0.00001695578,0.00000281311,0.00005933028,0.00001375179],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9836338,"threshold_uncertainty_score":0.9997557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1713453129845609,"score_gpt":0.4552920282500601,"score_spread":0.2839467152654992,"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."}}