{"id":"W3036380211","doi":"10.18280/jesa.530211","title":"Dynamic Intuitionistic Fuzzy Multiple Attributes Decision Making Method Based on Prospect Theory and VIKOR","year":2020,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Evaluation Methods in Various Fields","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Science Foundation of Guangxi Province","keywords":"VIKOR method; Computer science; Fuzzy logic; Mathematics; Mathematical optimization; Operations research; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004011788,0.0002704251,0.000351854,0.00009493472,0.0006507975,0.0003254693,0.0003606032,0.0001151025,0.001680222],"category_scores_gemma":[0.007223971,0.0002246861,0.0001161469,0.0004098195,0.0001922437,0.0002743638,0.0002118358,0.0005311261,0.0002934614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004108425,"about_ca_system_score_gemma":0.00004342361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005455412,"about_ca_topic_score_gemma":0.00001176613,"domain_scores_codex":[0.9958276,0.001929877,0.0006274058,0.0004511703,0.0008135087,0.0003504736],"domain_scores_gemma":[0.9955213,0.00352274,0.0003962478,0.0002659308,0.00004663919,0.0002471588],"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":[0.0003132075,0.0001025522,0.02163091,0.0001036612,0.00004483402,0.0001369845,0.001165264,0.06904134,0.004685976,0.001841347,0.001141909,0.899792],"study_design_scores_gemma":[0.0005919923,0.0003687686,0.3157133,0.0002438991,0.00005167854,0.0001920375,0.00006291112,0.6158246,0.0001468805,0.0664058,0.0001706572,0.000227452],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09008887,0.0001285646,0.9057035,0.000627974,0.0002105718,0.000375507,0.00001645137,0.000169204,0.002679377],"genre_scores_gemma":[0.5637873,0.00001674049,0.435127,0.0009305209,0.00004364838,0.000009661205,0.000001684435,0.00003168476,0.00005167204],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8995646,"threshold_uncertainty_score":0.9992324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02964467014663971,"score_gpt":0.3275860271205056,"score_spread":0.2979413569738658,"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."}}