{"id":"W4382541166","doi":"10.18280/mmep.100322","title":"SCOR Racetrack to Improve Supply Chain Performance","year":2023,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Computer science; Business; Marketing","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":[0.005373674,0.0009432021,0.0007995763,0.001940575,0.0008030155,0.002377509,0.001445039,0.001115113,0.007086158],"category_scores_gemma":[0.007115255,0.0005371368,0.000973202,0.002426044,0.0006857648,0.003385456,0.002760497,0.001281753,0.0009604933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001982571,"about_ca_system_score_gemma":0.004933306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007649992,"about_ca_topic_score_gemma":0.009748253,"domain_scores_codex":[0.9976417,0.0009501516,0.0001039392,0.0002839193,0.0007991684,0.0002211056],"domain_scores_gemma":[0.9968601,0.001102722,0.0006633645,0.0004992478,0.0007447316,0.000129757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001999455,0.0003130969,0.003908452,0.0002110102,0.0000710594,0.00008110124,0.0001960315,0.7324631,0.005573135,0.04552492,0.002640334,0.2088178],"study_design_scores_gemma":[0.00003908649,0.0006310948,0.001431968,0.00007256818,0.00001932686,0.00004475121,0.0001540708,0.9671345,0.005486923,0.01613779,0.008811768,0.00003620806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05038571,0.0003040257,0.9297863,0.00045571,0.00005082714,0.0004212332,0.000179074,0.001667926,0.01674917],"genre_scores_gemma":[0.4169365,0.0003853609,0.575565,0.0001182322,0.00001849569,0.0004231771,0.0005033196,0.000176497,0.00587331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007649992,"threshold_uncertainty_score":0.02841902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01591759871505453,"score_gpt":0.1997098334477974,"score_spread":0.1837922347327429,"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."}}