{"id":"W4387298612","doi":"10.37702/2175-957x.cobenge.2023.4506","title":"IMPACTOS DA UTILIZAÇÃO DA INTELIGÊNCIA ARTIFICIAL NA EDUCAÇÃO EM ENGENHARIA: UMA ABORDAGEM EXPLORATÓRIA","year":2023,"lang":"pt","type":"article","venue":"","topic":"Business and Management Studies","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003980091,0.0009942784,0.00138312,0.001530446,0.001393118,0.00305477,0.002169585,0.0003586148,0.0129578],"category_scores_gemma":[0.003083682,0.0007728082,0.000564748,0.008036554,0.000305103,0.001603701,0.003020952,0.0005645775,0.02907083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001378461,"about_ca_system_score_gemma":0.0003642031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003288454,"about_ca_topic_score_gemma":0.000458609,"domain_scores_codex":[0.9910064,0.0003894938,0.002069202,0.002061965,0.002690022,0.001782904],"domain_scores_gemma":[0.9946931,0.001171691,0.0006172522,0.00202034,0.0009930306,0.0005045675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001981812,0.0004407648,0.00112507,0.00009216986,0.0004462892,0.0001719683,0.01017422,0.0001425822,0.0002585144,0.01698973,0.3239765,0.6459841],"study_design_scores_gemma":[0.002937153,0.0009830151,0.02824254,0.0006453069,0.001124044,0.00002053288,0.503773,0.1730888,0.001878705,0.05555056,0.2264642,0.005292123],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4668437,0.005282679,0.3398196,0.05708439,0.0775727,0.006626752,0.000825839,0.004282147,0.04166222],"genre_scores_gemma":[0.9623238,0.001112648,0.0001712185,0.001535016,0.000586338,0.0001546118,0.00005660091,0.0001066886,0.03395307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6406919,"threshold_uncertainty_score":0.999907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3067371963839866,"score_gpt":0.4262702374386877,"score_spread":0.1195330410547011,"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."}}