{"id":"W4386077567","doi":"10.5267/j.uscm.2023.8.009","title":"Inventory competition, artificial intelligence, and quality improvement decisions in supply chains with digital marketing","year":2023,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Marketing; Competition (biology); Supply chain; Quality (philosophy); Supply chain management; Business; Respondent; Quality management; Service (business); Product (mathematics); Industrial organization","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":[0.004892899,0.0001833862,0.0002212767,0.001355912,0.001298116,0.003397119,0.0003336886,0.0006439534,0.002780336],"category_scores_gemma":[0.01434985,0.0002029769,0.0002622143,0.001583294,0.001837661,0.002177669,0.001798814,0.0007728802,0.0001145162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004007671,"about_ca_system_score_gemma":0.002507591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025675,"about_ca_topic_score_gemma":0.01619044,"domain_scores_codex":[0.9969097,0.00147995,0.0001512348,0.0002205506,0.0006867048,0.000551877],"domain_scores_gemma":[0.9734547,0.01499429,0.007621992,0.0003799155,0.001355524,0.00219361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004574799,0.0009322169,0.9344067,0.0001051726,0.0001060545,0.0003803338,0.008731183,0.005096243,0.001279788,0.01100062,0.0004708505,0.03703339],"study_design_scores_gemma":[0.00008312714,0.0008906804,0.9349036,0.0001264001,0.00009749702,0.0002190982,0.02675501,0.0194751,0.0009513923,0.01229775,0.004110215,0.0000900289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952425,0.000178537,0.0003951969,0.0003121744,0.000003119625,0.00001347276,0.00001026177,0.000002481976,0.003842318],"genre_scores_gemma":[0.9995393,0.00004763078,0.0001630117,0.00003717205,0.000004706273,0.000003743111,0.000008524886,9.326586e-7,0.0001951032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01025675,"threshold_uncertainty_score":0.02907777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04233702146293768,"score_gpt":0.2689551576795026,"score_spread":0.2266181362165649,"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."}}