{"id":"W4386835796","doi":"10.47852/bonviewglce32021009","title":"Providing a Green Value Stream Map to Improve Production Performance","year":2023,"lang":"en","type":"article","venue":"Green and Low-Carbon Economy","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Value stream mapping; Production (economics); Pollution; Environmental pollution; Environmental science; Process (computing); Stage (stratigraphy); Environmental impact assessment; Triple bottom line; Environmental resource management; Value (mathematics); Environmental economics; Business; Environmental planning; Computer science; Environmental protection; Sustainability; Economics; Ecology; Geology","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":[0.001412479,0.001138225,0.0005928472,0.00337629,0.0006774034,0.00399286,0.0008527438,0.0006941133,0.012825],"category_scores_gemma":[0.004897554,0.0004410246,0.0007692545,0.003067048,0.0004476972,0.004012122,0.001763874,0.0009018655,0.002620522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072287,"about_ca_system_score_gemma":0.002119854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004617743,"about_ca_topic_score_gemma":0.006614804,"domain_scores_codex":[0.9991497,0.0001837183,0.00004217183,0.0001138083,0.0004265683,0.00008415207],"domain_scores_gemma":[0.9982212,0.0006087318,0.0002494126,0.0001627232,0.000653443,0.0001044866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005548747,0.0004543502,0.02728986,0.001603415,0.000139559,0.0005163421,0.001393519,0.1934787,0.03180546,0.02800982,0.03155973,0.6831944],"study_design_scores_gemma":[0.00008512591,0.0005646914,0.02542811,0.0008219158,0.0001977753,0.0002930938,0.002647288,0.6964187,0.05849686,0.06634182,0.1484051,0.0002994375],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1286178,0.002395742,0.7933052,0.003317504,0.0005594689,0.0006057683,0.00496726,0.01043473,0.05579657],"genre_scores_gemma":[0.5124474,0.002112808,0.4719369,0.0001783899,0.000079832,0.0003753532,0.003241197,0.001073868,0.008554296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.012825,"threshold_uncertainty_score":0.04290396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01624991290279083,"score_gpt":0.2111668233895022,"score_spread":0.1949169104867114,"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."}}