{"id":"W2571664187","doi":"10.1108/mrr-09-2015-0208","title":"Emissions from international transport in global supply chains","year":2017,"lang":"en","type":"article","venue":"Management Research Review","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Supply chain; Business; Sustainability; Greenhouse gas; Industrial organization; Environmental economics; Originality; Carbon tax; Supply chain management; Economics; Marketing","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":[0.001287005,0.0008161946,0.0004010513,0.002157305,0.0005269683,0.00265964,0.0004210556,0.0007985663,0.002827706],"category_scores_gemma":[0.002022053,0.0002347143,0.0009540425,0.004156283,0.001078741,0.003060421,0.001259642,0.0007463952,0.0002330798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003397221,"about_ca_system_score_gemma":0.001835157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01336643,"about_ca_topic_score_gemma":0.01383002,"domain_scores_codex":[0.9985469,0.0006064879,0.00006523074,0.0001238123,0.0005485087,0.0001090727],"domain_scores_gemma":[0.9986026,0.0006712793,0.00025274,0.0000830396,0.0003645549,0.00002590621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001065356,0.0001203339,0.02971619,0.003186186,0.0004511534,0.0007926216,0.0007910008,0.3510877,0.002633181,0.2978979,0.003487713,0.3097294],"study_design_scores_gemma":[0.00003234834,0.0004631882,0.04371228,0.007390466,0.0006632732,0.001132317,0.00753968,0.1253693,0.01639486,0.3856527,0.4113881,0.0002613718],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3867638,0.1468445,0.2126039,0.007821023,0.001742662,0.0005039938,0.001429992,0.0002508932,0.2420392],"genre_scores_gemma":[0.9046944,0.06838911,0.01461323,0.0003509959,0.0001737546,0.00009958188,0.0003180126,0.00006575792,0.01129514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01336643,"threshold_uncertainty_score":0.02657723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06766960237017319,"score_gpt":0.4083958293268085,"score_spread":0.3407262269566352,"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."}}