{"id":"W4392640011","doi":"10.57209/e-locucao.v1i20.390","title":"A UTILIZAÇÃO DA INTELIGÊNCIA ARTIFICIAL NOS TRABALHOS DE AUDITORIA INDEPENDENTE","year":2021,"lang":"pt","type":"article","venue":"Revista Científica e-Locução","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational and Environmental Medical Association of Canada","funders":"","keywords":"Philosophy; Humanities","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":[0.008607719,0.0008810527,0.0008471499,0.003344127,0.001146163,0.009400491,0.001793576,0.001485171,0.004570435],"category_scores_gemma":[0.03574941,0.0006051337,0.001152579,0.003153045,0.002675971,0.005960103,0.003427116,0.001380804,0.001323423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001897397,"about_ca_system_score_gemma":0.002045297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003092886,"about_ca_topic_score_gemma":0.002546569,"domain_scores_codex":[0.9902062,0.004214657,0.0006460926,0.001424448,0.003145691,0.0003629983],"domain_scores_gemma":[0.9689924,0.01770827,0.00223039,0.005479424,0.004949645,0.0006398467],"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":[0.0005155028,0.0002300553,0.01914064,0.001767946,0.0002829032,0.0004128184,0.007354506,0.03408607,0.02061988,0.05617111,0.003143787,0.8562747],"study_design_scores_gemma":[0.0001418179,0.001762616,0.06200545,0.002550497,0.0007918075,0.002044143,0.008849562,0.5041344,0.0627639,0.1572502,0.1971905,0.0005151554],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1864668,0.006810141,0.7485983,0.002674966,0.0004801757,0.0004217236,0.0003566593,0.002470716,0.05172049],"genre_scores_gemma":[0.7699801,0.003095208,0.2147959,0.0003543414,0.0001982698,0.0002285868,0.0002643843,0.000200951,0.01088228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009400491,"threshold_uncertainty_score":0.04552251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08202005504977644,"score_gpt":0.3156217217567132,"score_spread":0.2336016667069367,"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."}}