{"id":"W2604361145","doi":"10.32920/ryerson.14663991.v1","title":"A framework for reducing greenhouse gas (GHG) emissions through carbon pricing for offshore outsourcing","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Western University","funders":"","keywords":"Greenhouse gas; Supply chain; Outsourcing; Business; Profit (economics); Natural resource economics; Carbon price; Environmental economics; Industrial organization; Offshore outsourcing; Offshoring; Economics; Microeconomics; 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":[0.002767238,0.002025935,0.0007988479,0.002743066,0.001570104,0.003104714,0.002628564,0.003323407,0.005375119],"category_scores_gemma":[0.001923489,0.0006334906,0.002404834,0.0021823,0.002599821,0.003826195,0.00241066,0.002659276,0.0009587046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004151141,"about_ca_system_score_gemma":0.008770909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008106334,"about_ca_topic_score_gemma":0.008969855,"domain_scores_codex":[0.9983557,0.0007549315,0.00007263807,0.0002301926,0.0004215059,0.0001650425],"domain_scores_gemma":[0.9993019,0.0002289607,0.0001054308,0.00006022162,0.0002425596,0.00006098515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008999153,0.00008480339,0.0001769134,0.0002820699,0.00001994412,0.0001966129,0.0001227177,0.05196612,0.0007298803,0.9324471,0.00334966,0.0106152],"study_design_scores_gemma":[0.00004113856,0.0001851309,0.0006094244,0.0005381007,0.00005899878,0.0002012217,0.0004528745,0.1284366,0.0008874319,0.8137199,0.05477386,0.00009521753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008617746,0.005157655,0.8798312,0.01469088,0.0005673802,0.0009187559,0.0004993184,0.0002009727,0.08951608],"genre_scores_gemma":[0.3747161,0.01395266,0.5841526,0.002092247,0.0005277602,0.002907025,0.0003616094,0.0001386967,0.02115117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008106334,"threshold_uncertainty_score":0.03011876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03599488088667359,"score_gpt":0.283766104944975,"score_spread":0.2477712240583014,"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."}}