{"id":"W4311715245","doi":"10.1007/s12008-022-01136-0","title":"RETRACTED ARTICLE: Green manufacturing via machine learning enabled approaches","year":2022,"lang":"en","type":"article","venue":"International Journal on Interactive Design and Manufacturing (IJIDeM)","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":8,"is_retracted":true,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Set (abstract data type); Perspective (graphical); Work (physics); Manufacturing engineering; Production (economics); Industrial engineering; Risk analysis (engineering); Machine learning; Artificial intelligence; Engineering; Business; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.003409783,0.001257289,0.001510342,0.002746342,0.002512039,0.00505355,0.003791272,0.01597342,0.03371607],"category_scores_gemma":[0.03472472,0.0005683974,0.00136819,0.001410535,0.002478532,0.002919962,0.002609906,0.009969389,0.02050903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003195692,"about_ca_system_score_gemma":0.00307571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004207197,"about_ca_topic_score_gemma":0.006476504,"domain_scores_codex":[0.9955446,0.0005503051,0.0004233822,0.0004984101,0.002557943,0.0004253938],"domain_scores_gemma":[0.9764076,0.008604493,0.0009715362,0.001218883,0.01064078,0.002156687],"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":[0.00007763888,0.00003070462,0.0001708076,0.0001811843,0.00001962755,0.0009766467,0.00006895231,0.0001029596,0.0002481525,0.0009873706,0.981797,0.01533909],"study_design_scores_gemma":[0.00003668353,0.00008226181,0.0009780508,0.0002776132,0.00004419682,0.001312513,0.0002203791,0.0007073283,0.0008589893,0.003893233,0.9915472,0.00004169219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.0006471336,0.002174676,0.00148336,0.1808735,0.8096586,0.00002733141,0.0003551852,0.0003779209,0.004402236],"genre_scores_gemma":[0.02015246,0.00746147,0.003625271,0.1922077,0.6238351,0.00009938915,0.0008312812,0.0006320653,0.1511552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9840266,"threshold_uncertainty_score":0.1127915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02962534495347667,"score_gpt":0.2289108181779644,"score_spread":0.1992854732244877,"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."}}