{"id":"W4387352975","doi":"10.5267/j.ac.2023.9.002","title":"Application of TOPSIS, VIKOR and COPRAS for ideal investment decisions","year":2023,"lang":"en","type":"article","venue":"Accounting","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"TOPSIS; Investment (military); Ranking (information retrieval); Business; VIKOR method; Industrial organization; Finance; Operations research; Multiple-criteria decision analysis; Engineering; Computer science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004662011,0.0001233186,0.0003046793,0.0004736615,0.0002315868,0.0003021327,0.0005331275,0.00007766146,0.00004364311],"category_scores_gemma":[0.01336048,0.00009923103,0.00008476046,0.00116078,0.00006856543,0.0003570493,0.0003749517,0.00006554914,0.0001702066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002319069,"about_ca_system_score_gemma":0.00004412225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006018406,"about_ca_topic_score_gemma":0.00003142667,"domain_scores_codex":[0.9972374,0.00005423671,0.0009109513,0.0005174194,0.001014196,0.0002658142],"domain_scores_gemma":[0.9917243,0.006673877,0.0004646986,0.0005855722,0.0004764229,0.00007509554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006767818,0.00005069574,0.06169804,0.00002092994,0.00002514316,0.00000243218,0.0009947178,0.0003518821,0.05276456,0.02539293,0.02485208,0.8337789],"study_design_scores_gemma":[0.001442561,0.00007455426,0.233292,0.0001123434,0.0000363969,0.00001190252,0.002565427,0.2015163,0.003145978,0.2278611,0.3295028,0.0004386642],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8968873,0.0001207103,0.1006678,0.0005829409,0.0003387444,0.0005785034,0.00003667132,0.0000807777,0.000706578],"genre_scores_gemma":[0.9720414,0.0000126957,0.02703411,0.0004791191,0.0001125009,0.00009088054,0.00001052335,0.00001790286,0.0002008772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8333402,"threshold_uncertainty_score":0.9949504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1885090671571325,"score_gpt":0.4565919228011663,"score_spread":0.2680828556440338,"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."}}