{"id":"W7153281641","doi":"10.63282/3050-9416.ijaibdcms-v5i4p123","title":"An Initiative-Scale Structure for Reliable AI: Governance-Centrical Architecture for Reliability, Difficult, and Active Policy","year":2024,"lang":"","type":"article","venue":"International Journal of AI BigData Computational and Management Studies","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Interoperability; Enterprise architecture; Enterprise system; Architecture; Software architecture; Enterprise software; Reference architecture; Corporate governance; Software","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008085588,0.0003769465,0.0006023691,0.0006438067,0.0004081861,0.001120719,0.001027006,0.0001045621,0.00001033811],"category_scores_gemma":[0.0006406078,0.0002966263,0.0002571229,0.0006568928,0.0004514735,0.001627266,0.0009899914,0.0004890279,0.000001021502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003796296,"about_ca_system_score_gemma":0.0003848601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002284674,"about_ca_topic_score_gemma":0.00001940719,"domain_scores_codex":[0.9963706,0.0001327125,0.0009394939,0.0008586682,0.00129612,0.0004024187],"domain_scores_gemma":[0.9944884,0.001605331,0.0003592206,0.0002251763,0.003105779,0.0002160556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001872538,0.001029147,0.001335447,0.002974964,0.009224035,0.0001337924,0.006097605,0.09348651,0.00003709111,0.2677304,0.03346468,0.5826138],"study_design_scores_gemma":[0.003106313,0.001439684,0.0129481,0.001182954,0.0005017393,0.0001591789,0.0008432157,0.4253131,0.00007079934,0.4595976,0.094282,0.0005552345],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01177052,0.006872789,0.8671168,0.1095542,0.001545029,0.001031692,0.002036638,0.00004001501,0.00003233523],"genre_scores_gemma":[0.898253,0.01520334,0.08063,0.003197628,0.002132433,0.00007969816,0.0002191913,0.00003823924,0.0002465305],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8864824,"threshold_uncertainty_score":0.9999486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02724562866597612,"score_gpt":0.3730370554082643,"score_spread":0.3457914267422882,"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."}}