{"id":"W7149039814","doi":"10.71465/ajbd793","title":"Big Data in Supply Chain Optimization: Opportunities and Challenges","year":2024,"lang":"","type":"article","venue":"American Journal Of Big Data","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Big data; Supply chain; Supply chain management; Competitive advantage; Supply chain risk management; Service management; Distribution (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":[0.01125011,0.001544809,0.002291607,0.002174294,0.002025554,0.009759546,0.003855104,0.004818543,0.002366534],"category_scores_gemma":[0.02351852,0.001153112,0.001173232,0.007746496,0.004257559,0.02206918,0.004042788,0.00686253,0.0006500339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002632465,"about_ca_system_score_gemma":0.00402041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005239269,"about_ca_topic_score_gemma":0.005696762,"domain_scores_codex":[0.9936817,0.003275005,0.0003081782,0.0006687543,0.00173757,0.0003288135],"domain_scores_gemma":[0.9590093,0.03139287,0.002005669,0.002167494,0.003885886,0.001538818],"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":[0.0003292534,0.0004591738,0.01175654,0.002586798,0.0003694128,0.0005383221,0.0008866639,0.1782132,0.0006797898,0.4058056,0.06597074,0.3324046],"study_design_scores_gemma":[0.00004551531,0.00006216489,0.001605178,0.0008452754,0.0000520322,0.0001316334,0.002782782,0.2354528,0.000617978,0.6981022,0.06020777,0.00009464075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.05088062,0.1869107,0.3263221,0.393008,0.005407927,0.00032039,0.00231698,0.0007016584,0.03413161],"genre_scores_gemma":[0.6849219,0.1314645,0.1557669,0.01397654,0.007939809,0.0003558704,0.001894194,0.0002188608,0.003461328],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01125011,"threshold_uncertainty_score":0.059497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3625181497620852,"score_gpt":0.3260290091661276,"score_spread":0.03648914059595754,"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."}}