{"id":"W4379280550","doi":"10.5267/j.uscm.2023.4.013","title":"The moderating effect of strategic momentum on the relationship between big data analytics capabilities and lean supply chain practices","year":2023,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Big data; Business; Analytics; Sample (material); Marketing; Knowledge management; Strategic planning; Process management; Supply chain management; Computer science; Data science","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":[0.006807912,0.0005028946,0.0003836734,0.001287537,0.001116029,0.003184436,0.0004353649,0.0005587164,0.004858625],"category_scores_gemma":[0.02662694,0.000322156,0.0005373908,0.001384779,0.001670261,0.002246741,0.002896769,0.001544104,0.0002726442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001264576,"about_ca_system_score_gemma":0.005362388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00305617,"about_ca_topic_score_gemma":0.00531986,"domain_scores_codex":[0.9939832,0.002775078,0.0004627165,0.0005323092,0.001138872,0.001107806],"domain_scores_gemma":[0.9281213,0.04727492,0.01354827,0.001800368,0.00389795,0.005357151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002250109,0.0003284551,0.9811187,0.00006023618,0.000103717,0.0002375921,0.003304842,0.0003144445,0.0006174035,0.00183776,0.00009577001,0.01175607],"study_design_scores_gemma":[0.00002214105,0.0005468919,0.9805346,0.0001358772,0.0001033032,0.0001335204,0.01362781,0.001270261,0.0007880988,0.001763799,0.001047337,0.0000263785],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957021,0.0001037821,0.0005832108,0.0003761565,0.00001350861,0.0000272392,0.00004290203,0.00000496483,0.003146105],"genre_scores_gemma":[0.9992499,0.00006125528,0.0003184197,0.00003994615,0.000009119429,0.00002016395,0.00002459486,0.000001834534,0.0002746311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006807912,"threshold_uncertainty_score":0.03600407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1311249242253311,"score_gpt":0.3038389291408288,"score_spread":0.1727140049154978,"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."}}