{"id":"W4293214428","doi":"10.5267/j.ijdns.2022.4.008","title":"Data quality analytics, business ethics, and cyber risk management on operational performance and fintech sustainability","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; LISREL; Structural equation modeling; Operational risk management; Analytics; Accounting; Risk management; Operational risk; Quality (philosophy); Sustainability; Descriptive statistics; Knowledge management; Process management; Computer science; Finance; Data science; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006497364,0.0003115584,0.0002459335,0.001287033,0.001078571,0.003027808,0.0003553416,0.0004143782,0.002280812],"category_scores_gemma":[0.02301087,0.0001213181,0.0003106454,0.001268649,0.002324436,0.00164005,0.002563412,0.001071784,0.0002620566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00180568,"about_ca_system_score_gemma":0.003767466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002095784,"about_ca_topic_score_gemma":0.002178718,"domain_scores_codex":[0.9910038,0.003209671,0.0006020238,0.0005965566,0.003592077,0.0009958633],"domain_scores_gemma":[0.9442589,0.02428363,0.01742586,0.00211717,0.006597306,0.005317114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001126379,0.000810782,0.9476124,0.00007492099,0.00005041454,0.0002549378,0.005293549,0.0009311818,0.0009392247,0.002146535,0.0003110466,0.04146245],"study_design_scores_gemma":[0.000008139805,0.0006232899,0.9746902,0.0001016373,0.00003620485,0.0001917011,0.01456021,0.003052797,0.00180421,0.002230115,0.002664605,0.00003685793],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925855,0.00005384234,0.0006574076,0.0003336751,0.000005599291,0.00002707828,0.00002183084,0.000008709052,0.006306474],"genre_scores_gemma":[0.9994173,0.00002953145,0.0002321643,0.00002588428,0.000004152535,0.000007207169,0.00001303023,0.000001669616,0.0002690581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006497364,"threshold_uncertainty_score":0.03436178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06215650915473732,"score_gpt":0.38296671872973,"score_spread":0.3208102095749927,"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."}}