{"id":"W4390271771","doi":"10.18280/ria.370619","title":"Enhancing Operational Efficiency in E-Commerce Through Artificial Intelligence and Information Management Integration","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information integration; Computer science; Knowledge management; Information management; Engineering management; Process management; Artificial intelligence; Business; Engineering; Data mining","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":[0.004524753,0.0008398736,0.0007395455,0.00218785,0.0007708707,0.006371439,0.001137841,0.001140293,0.001215247],"category_scores_gemma":[0.006166189,0.0003702482,0.0007567003,0.002686983,0.002090465,0.006008791,0.002058811,0.001239635,0.000311474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002068548,"about_ca_system_score_gemma":0.002230457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001785438,"about_ca_topic_score_gemma":0.001818753,"domain_scores_codex":[0.9958615,0.002037629,0.0002717383,0.0002830052,0.001269198,0.0002769842],"domain_scores_gemma":[0.9966567,0.002088899,0.0004143475,0.0003584661,0.0003866337,0.0000950745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002018527,0.0007341243,0.00827986,0.000519564,0.0002144049,0.0003085899,0.001325331,0.2924819,0.006821519,0.34784,0.00164826,0.3396246],"study_design_scores_gemma":[0.00005606811,0.0004655759,0.004606591,0.0003298353,0.0001362793,0.0002050204,0.002111903,0.7461651,0.007163187,0.2193895,0.01928952,0.00008148913],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1507159,0.00246083,0.7847999,0.002635046,0.00009660376,0.0003273987,0.00005867327,0.0003710819,0.05853463],"genre_scores_gemma":[0.8666217,0.001115352,0.1300011,0.000161476,0.00004789071,0.0001074848,0.00005739053,0.00002646986,0.001860985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006371439,"threshold_uncertainty_score":0.02392948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07597255048907,"score_gpt":0.2985497808358963,"score_spread":0.2225772303468263,"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."}}