{"id":"W3005271014","doi":"10.3390/su12031101","title":"Green Supply Chain Performance Prediction Using a Bayesian Belief Network","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Supply chain; Supply chain management; Bayesian network; Competitive advantage; Business; Supply chain risk management; Performance indicator; Environmental economics; Service management; Computer science; Marketing; Economics; Artificial intelligence","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":[0.002754599,0.0007816625,0.0006793225,0.002592436,0.0004613622,0.001641769,0.0009812359,0.001186595,0.001440441],"category_scores_gemma":[0.009676488,0.0005620069,0.0007189459,0.001932407,0.0004314094,0.002067566,0.0006842216,0.0008664816,0.0002837345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001792118,"about_ca_system_score_gemma":0.00105676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02167834,"about_ca_topic_score_gemma":0.01578973,"domain_scores_codex":[0.9989889,0.0004319121,0.00005960906,0.0001761243,0.0002481253,0.00009520679],"domain_scores_gemma":[0.9957075,0.00317384,0.0004480463,0.00008163476,0.000516393,0.00007261078],"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":[0.00008209796,0.00009809118,0.01060388,0.00007733174,0.00008443627,0.00005907151,0.00007561127,0.9563178,0.0005235453,0.004272477,0.0005196633,0.027286],"study_design_scores_gemma":[0.000003019584,0.00001185379,0.0008714466,0.00001016606,0.00001191067,0.000005266735,0.00001147756,0.9968088,0.0001107733,0.002065458,0.00008274251,0.000007085516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2603506,0.0008081731,0.7299799,0.000942662,0.00004173564,0.0001461246,0.000730899,0.0003621767,0.006637793],"genre_scores_gemma":[0.9616055,0.0005507643,0.0362413,0.00005133454,0.00002048032,0.00009624191,0.0004566349,0.00001156037,0.0009661122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02167834,"threshold_uncertainty_score":0.04310429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01259357919690322,"score_gpt":0.2120544854266889,"score_spread":0.1994609062297857,"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."}}