{"id":"W2167621333","doi":"10.1504/ijor.2011.039711","title":"Trade-off model for carbon market sensitive green supply chain network design","year":2011,"lang":"en","type":"article","venue":"International Journal of Operational Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Greenhouse gas; Supply chain; Carbon footprint; Supply chain network; Environmental economics; Network planning and design; Integer programming; Business; Operations research; Computer science; Supply chain management; Industrial organization; Economics; Marketing; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005780735,0.000174413,0.0002152441,0.0008693776,0.0002225461,0.0003590316,0.0008251659,0.00007620554,0.0004682786],"category_scores_gemma":[0.0007967979,0.0001597248,0.0001449358,0.0003531164,0.0001098986,0.001088951,0.0002651112,0.0003610367,0.0000138419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003227093,"about_ca_system_score_gemma":0.0003337552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002696177,"about_ca_topic_score_gemma":0.00003719215,"domain_scores_codex":[0.9967858,0.0001149227,0.0005730446,0.0002546642,0.001790612,0.0004809957],"domain_scores_gemma":[0.9955868,0.0004497459,0.0002497348,0.0001411382,0.003531151,0.0000414507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008490607,0.0008902849,0.005098083,0.0001662584,0.001556233,0.001083855,0.002288779,0.3212332,0.0006561379,0.3077503,0.322909,0.02787726],"study_design_scores_gemma":[0.001287125,0.00008411341,0.002946477,0.00008319708,0.00003087436,0.00002747693,0.0008185358,0.9354932,0.0001153373,0.04179484,0.01711769,0.0002011633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06982711,0.0008074624,0.6899693,0.08670017,0.005279259,0.006316926,0.00008806559,0.0001447917,0.1408669],"genre_scores_gemma":[0.973129,0.00004331465,0.01502511,0.001569311,0.005242583,0.00007879412,0.00003140301,0.00004869983,0.00483183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9033018,"threshold_uncertainty_score":0.6513391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09181791917536908,"score_gpt":0.3252257046168983,"score_spread":0.2334077854415292,"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."}}