{"id":"W7153116829","doi":"10.63282/3050-9262.ijaidsml-v5i3p121","title":"AI-Augmented Software Engineering: A Holistic Approach to Reliability, Security, and Lifecycle Optimization","year":2024,"lang":"","type":"article","venue":"International Journal of Artificial Intelligence Data Science and Machine Learning","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":"Software quality; Software development; Quality (philosophy); Vulnerability (computing); Implementation; Model-driven architecture; Software system; Software; System lifecycle","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":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008200362,0.0003138618,0.0004139277,0.00162935,0.0004667047,0.00505755,0.003894861,0.000108735,0.000043175],"category_scores_gemma":[0.0174211,0.0002821293,0.00009710302,0.00259247,0.0007600026,0.005047884,0.003780766,0.001320659,0.00001847884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002587611,"about_ca_system_score_gemma":0.0009429038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002598566,"about_ca_topic_score_gemma":0.000009561028,"domain_scores_codex":[0.9941794,0.000192291,0.001184922,0.001239108,0.002665868,0.0005384528],"domain_scores_gemma":[0.9953576,0.0008149042,0.0002560711,0.0006166713,0.002354736,0.0005999888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009914259,0.0003646218,0.001289556,0.0002096304,0.0001665802,0.0001112488,0.003952292,0.6624794,0.0004402515,0.008440008,0.0001332659,0.322314],"study_design_scores_gemma":[0.00004582907,0.0002788161,0.0001238909,0.0004233291,0.00005612506,0.0003049034,0.0003130967,0.9933483,0.0002991189,0.001835994,0.002696964,0.0002736329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01321387,0.001881621,0.9766424,0.006445885,0.001432565,0.0002116771,0.00008549091,0.00006447735,0.00002201236],"genre_scores_gemma":[0.942488,0.001830173,0.05478963,0.0003054969,0.0005065959,0.000003748362,0.00003894187,0.00002047128,0.00001699513],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9292741,"threshold_uncertainty_score":0.9999631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0680045401483019,"score_gpt":0.3636618901234947,"score_spread":0.2956573499751928,"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."}}