{"id":"W4235008403","doi":"10.32920/ryerson.14662221.v1","title":"A dual factor decision making model in green manufacturing","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Remanufacturing; Product (mathematics); Computer science; Dual (grammatical number); Operations research; Quality (philosophy); Decision tree; Manufacturing engineering; Data mining; Engineering; Mathematics","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":[0.003881147,0.00171512,0.001929688,0.00135529,0.0009383811,0.003589746,0.00188348,0.002566151,0.007082016],"category_scores_gemma":[0.005027083,0.0009948967,0.001822162,0.001402198,0.001663717,0.002003751,0.001765856,0.002415775,0.0006895534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003982794,"about_ca_system_score_gemma":0.002295286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01466279,"about_ca_topic_score_gemma":0.00807769,"domain_scores_codex":[0.9978955,0.001012093,0.00007569863,0.0003690587,0.0003288665,0.0003187764],"domain_scores_gemma":[0.9968839,0.002233351,0.0002851668,0.00007983036,0.0003274534,0.0001902503],"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":[0.00009464355,0.00005325853,0.0003456869,0.00004968456,0.00003330311,0.0001037882,0.00006011769,0.9631468,0.0002683239,0.0320536,0.0002242606,0.003566599],"study_design_scores_gemma":[0.00001721067,0.00003350015,0.00007456927,0.000008438115,0.00001135202,0.000009378666,0.00001716554,0.9887637,0.0000778353,0.01061233,0.0003637726,0.0000107849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1053602,0.001227211,0.8587019,0.00147804,0.0001875883,0.0002776071,0.0005815136,0.0002369726,0.03194894],"genre_scores_gemma":[0.9038421,0.0008866757,0.07586557,0.0001768911,0.00007370094,0.0003601413,0.0002488387,0.00005250999,0.01849363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01466279,"threshold_uncertainty_score":0.02915484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02567968019503992,"score_gpt":0.2566563344695865,"score_spread":0.2309766542745466,"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."}}