{"id":"W4402285675","doi":"10.1016/j.aei.2024.102802","title":"A multi-phase integrated scheduling method for cloud remanufacturing systems","year":2024,"lang":"en","type":"article","venue":"Advanced Engineering Informatics","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Remanufacturing; Cloud computing; Computer science; Scheduling (production processes); Industrial engineering; Distributed computing; Systems engineering; Manufacturing engineering; Engineering; Operations management; Operating system","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":[0.0006599699,0.0009382667,0.0008950658,0.0006737695,0.0007811085,0.0007369396,0.001381116,0.0007876258,0.003940058],"category_scores_gemma":[0.0007501188,0.0004420811,0.001367135,0.0008709515,0.0003495049,0.0008849039,0.0008764451,0.0009789113,0.0005474584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009957915,"about_ca_system_score_gemma":0.002036837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009087441,"about_ca_topic_score_gemma":0.007654602,"domain_scores_codex":[0.9996425,0.0000887814,0.00001826616,0.00005927872,0.0001450032,0.00004622667],"domain_scores_gemma":[0.9998035,0.00006166474,0.00002975733,0.00001383474,0.00007482506,0.00001637086],"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":[0.00003573472,0.00003808849,0.0002440533,0.0001232824,0.00003347149,0.00006828445,0.00005671917,0.9323949,0.002864606,0.01315479,0.001219131,0.04976687],"study_design_scores_gemma":[0.000004629204,0.00001438694,0.00002806147,0.000004917148,0.000004910381,0.00000900986,0.000006321129,0.9974211,0.0002205857,0.001157603,0.001125152,0.00000328693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00221859,0.0002104954,0.9946951,0.00006148767,0.00005130633,0.00005046718,0.0000199057,0.0001189594,0.002573571],"genre_scores_gemma":[0.3229803,0.0009366246,0.6675007,0.0001342259,0.0001088337,0.0005402525,0.0001940664,0.0001711207,0.007433753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009087441,"threshold_uncertainty_score":0.01806909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170363785397346,"score_gpt":0.2678331510824212,"score_spread":0.2561295132284477,"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."}}