{"id":"W4388962178","doi":"10.1007/978-3-031-44742-6_6","title":"Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS) in Uncertainty Environment","year":2023,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"TOPSIS; Ideal solution; Similarity (geometry); Ideal (ethics); Order (exchange); Mathematical optimization; Computer science; Mathematics; Artificial intelligence; Mathematical economics; Economics; Chemistry; Philosophy; Epistemology","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":[0.002164042,0.0008611029,0.001037673,0.002057557,0.000733883,0.001532501,0.001257763,0.0006748089,0.005354723],"category_scores_gemma":[0.003293297,0.0003204825,0.001351526,0.003565478,0.0008380697,0.001972636,0.001088079,0.00219577,0.001203267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006772872,"about_ca_system_score_gemma":0.00124654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001274034,"about_ca_topic_score_gemma":0.001732757,"domain_scores_codex":[0.9979733,0.0005678955,0.0001267405,0.0001900174,0.00107829,0.00006382278],"domain_scores_gemma":[0.9992504,0.0004179535,0.00003682411,0.00007897395,0.0001988297,0.0000170471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007114468,0.0001321295,0.0003381832,0.001038495,0.000205904,0.0002596731,0.0009346018,0.02552517,0.0127356,0.326508,0.01107492,0.6211762],"study_design_scores_gemma":[0.00006977165,0.0004158077,0.0009836935,0.0003205027,0.0002374854,0.001424488,0.0007794067,0.4361243,0.01653495,0.4854417,0.0575196,0.000148365],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001775466,0.0004203158,0.9915757,0.0001293169,0.0001038916,0.00008999299,0.00005548592,0.0001861984,0.005663837],"genre_scores_gemma":[0.03334567,0.0006603627,0.9630486,0.00004757307,0.00005179589,0.0001427872,0.00008267627,0.0000349807,0.002585543],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005354723,"threshold_uncertainty_score":0.01791334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.517560907252382,"score_gpt":0.5014067748008166,"score_spread":0.01615413245156538,"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."}}