{"id":"W1978078915","doi":"10.1016/j.apm.2015.03.044","title":"Supply chain models with greenhouse gases emissions, energy usage and different coordination decisions","year":2015,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":173,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Università degli Studi di Brescia","keywords":"Greenhouse gas; Supply chain; Environmental economics; Energy (signal processing); Business; Environmental science; Economics; Physics; Marketing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00185917,0.001443253,0.001492312,0.001272644,0.0009738592,0.003275708,0.002302763,0.003448623,0.006663643],"category_scores_gemma":[0.004515816,0.001091897,0.001531348,0.003259102,0.001781058,0.003911757,0.001484183,0.002109726,0.000759469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003374652,"about_ca_system_score_gemma":0.002427034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02578456,"about_ca_topic_score_gemma":0.01489583,"domain_scores_codex":[0.9989247,0.0004682412,0.00005459771,0.0001804745,0.0001971774,0.0001748405],"domain_scores_gemma":[0.9970351,0.001965618,0.0003667706,0.0001291806,0.0003637467,0.0001395751],"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":[0.00001988709,0.00002260836,0.0001720373,0.00002381347,0.00001433698,0.00004328563,0.00003008562,0.9672236,0.0001372873,0.03122515,0.0002006319,0.0008871552],"study_design_scores_gemma":[0.00001303012,0.00001461113,0.00009548245,0.000004905301,0.00001128773,0.000007622277,0.00002205453,0.9846485,0.00007136242,0.01471088,0.000391353,0.000008772819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2351493,0.001580887,0.6927213,0.004672436,0.0003147018,0.0002271499,0.002720046,0.0004507027,0.0621634],"genre_scores_gemma":[0.9314513,0.00138396,0.02022695,0.0002340859,0.0001203306,0.0003115946,0.000788716,0.00007736153,0.04540566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02578456,"threshold_uncertainty_score":0.05126894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03917632093160499,"score_gpt":0.2186636658484858,"score_spread":0.1794873449168808,"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."}}