{"id":"W4401787228","doi":"10.1177/2694105820230301005","title":"AI in Personalized Product Recommendations","year":2023,"lang":"en","type":"article","venue":"Management and business review.","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada","funders":"","keywords":"Product (mathematics); Computer science; Mathematics","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":[0.003555845,0.0007741901,0.0009683463,0.002014137,0.001084713,0.002912623,0.001293726,0.003489917,0.008111378],"category_scores_gemma":[0.0127159,0.0006121242,0.0008088239,0.002985699,0.002449517,0.006674231,0.00149241,0.003919644,0.002830697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001661576,"about_ca_system_score_gemma":0.0008056831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005541166,"about_ca_topic_score_gemma":0.003975316,"domain_scores_codex":[0.9971788,0.001385508,0.0001300132,0.0005010599,0.0006736651,0.0001309522],"domain_scores_gemma":[0.9925683,0.006138564,0.0001621195,0.0004566031,0.0005307484,0.0001437004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001769941,0.0001395428,0.001909977,0.001197846,0.0002315297,0.0002935095,0.0006347266,0.02178853,0.000580955,0.5239868,0.07755307,0.3715065],"study_design_scores_gemma":[0.00008719115,0.0001334631,0.001342363,0.0005196659,0.0001093654,0.0004879629,0.0002521162,0.09482551,0.0006372782,0.7191342,0.1823928,0.00007816256],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.013733,0.2652074,0.4762197,0.0553831,0.005578674,0.0002849407,0.0005681685,0.001014978,0.1820101],"genre_scores_gemma":[0.4780981,0.1408908,0.2789896,0.01530262,0.009652379,0.000756163,0.0009536319,0.0002304842,0.07512607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008111378,"threshold_uncertainty_score":0.02713531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03554795690323863,"score_gpt":0.3102819259881712,"score_spread":0.2747339690849325,"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."}}