{"id":"W4226549776","doi":"","title":"ANALYSIS OF DIGITAL READINESS PERFORMANCES OF G20 COUNTRIES: AN APPLICATION WITH ENTROPY-BASED VIKOR METHOD","year":2021,"lang":"tr","type":"article","venue":"DergiPark (Istanbul University)","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"VIKOR method; Computer science; Industrial engineering; Engineering; Artificial intelligence; Fuzzy logic","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004836744,0.001204004,0.0009202093,0.01196091,0.000576262,0.002268537,0.0006568162,0.0006456625,0.003315768],"category_scores_gemma":[0.01192877,0.0003124031,0.002031315,0.01109113,0.0007089458,0.001353612,0.001591402,0.0008600656,0.0004738243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001092577,"about_ca_system_score_gemma":0.00122091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004138885,"about_ca_topic_score_gemma":0.003848986,"domain_scores_codex":[0.9968348,0.00122241,0.0003221678,0.00030644,0.001130895,0.0001832512],"domain_scores_gemma":[0.9933148,0.004478977,0.0009011125,0.0002967679,0.0009192908,0.00008909179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009442074,0.0006615788,0.3043801,0.002845297,0.001844753,0.002003907,0.01069993,0.1586611,0.01194975,0.03536489,0.004500736,0.4661437],"study_design_scores_gemma":[0.00008922149,0.0009000886,0.3172778,0.0007903813,0.0006108094,0.0008559652,0.01493149,0.6114923,0.01089606,0.02708858,0.01471815,0.0003492156],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6763083,0.001313103,0.2891286,0.0003330274,0.0001252726,0.001451044,0.002775559,0.0005595478,0.02800559],"genre_scores_gemma":[0.8864153,0.000469252,0.1093051,0.00003017907,0.00002111203,0.0007112537,0.001355152,0.00004598293,0.001646718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01196091,"threshold_uncertainty_score":0.02557939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129830277164576,"score_gpt":0.2287867241873042,"score_spread":0.2158036964708466,"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."}}