{"id":"W4394097787","doi":"10.6084/m9.figshare.24633105","title":"Customer Satisfaction Response to Artificial Intelligence Tools Usage During Online Shopping","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Customer satisfaction; Computer science; Business; World Wide Web; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000528026,0.0002681505,0.0002758671,0.00110545,0.0002356579,0.0006484974,0.0003698633,0.0005132887,0.00251379],"category_scores_gemma":[0.002375686,0.00008052213,0.0003645252,0.001927483,0.0001346192,0.0003384408,0.0003713531,0.0005156413,0.001275813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000575464,"about_ca_system_score_gemma":0.0002503841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01474843,"about_ca_topic_score_gemma":0.02562212,"domain_scores_codex":[0.9996029,0.0000886881,0.00005266531,0.00007908639,0.0001126141,0.00006409035],"domain_scores_gemma":[0.9986383,0.0004782347,0.0002381292,0.0001329786,0.0003979055,0.0001145335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001465868,0.001099852,0.8553975,0.0004240172,0.0001458,0.0003336227,0.0008454595,0.005461389,0.001614001,0.0009273511,0.08250981,0.04977538],"study_design_scores_gemma":[0.00004670273,0.0003074011,0.9637321,0.00003995539,0.00003825743,0.0002316812,0.001025675,0.01552552,0.001309223,0.0002366081,0.01745562,0.0000512781],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.8524898,0.00006894289,0.0003355888,0.0001780505,0.00001984737,0.00006729794,0.1438413,0.0001530859,0.002846217],"genre_scores_gemma":[0.7061274,0.0001030336,0.001650864,0.0000991564,0.00001242555,0.0002084421,0.2884776,0.00001841125,0.00330262],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01474843,"threshold_uncertainty_score":0.02932519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3484497990212087,"score_gpt":0.4462894306002897,"score_spread":0.09783963157908104,"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."}}