{"id":"W3156695649","doi":"10.1111/poms.13439","title":"Planning Production and Equipment Qualification under High Process Flexibility","year":2021,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada); University of British Columbia","funders":"Semiconductor Research Corporation","keywords":"Computer science; Flexibility (engineering); Schedule; Factory (object-oriented programming); Product (mathematics); Process (computing); Production (economics); Production schedule; Heuristic; Industrial engineering; Sequence (biology); Production planning; Mathematical optimization; Reliability engineering; Operations research; Scheduling (production processes); Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002314468,0.0001077077,0.00008627203,0.00008651105,0.0002504361,0.0001302811,0.00002869208,0.00003226102,0.00003157103],"category_scores_gemma":[0.00005776786,0.0001132578,0.00001038024,0.0002613533,0.00002867143,0.0002638478,0.00002358009,0.00007550588,0.000006337082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004754887,"about_ca_system_score_gemma":0.00001039769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000026708,"about_ca_topic_score_gemma":0.0000116528,"domain_scores_codex":[0.9991617,0.00003198368,0.00019961,0.000364082,0.00013274,0.0001098416],"domain_scores_gemma":[0.9996056,0.00000402203,0.00001678136,0.0002024029,0.0001263242,0.00004488741],"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":[0.000004166655,0.00005453026,0.0001638644,0.0001631067,0.00004468066,7.60381e-7,0.000788056,0.9878937,0.0004073353,0.004136152,0.0001943165,0.006149324],"study_design_scores_gemma":[0.001027424,0.00008081947,0.02348714,0.0004239894,0.0003049154,0.0001045107,0.02294464,0.8773548,0.06620144,0.003282821,0.003430342,0.001357177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7570243,0.001678874,0.227109,0.008695417,0.002274501,0.0008967455,0.000004489386,0.0007277565,0.001588894],"genre_scores_gemma":[0.9640083,0.0005141567,0.03336465,0.00007651117,0.0001795952,0.0001125529,0.00006366368,0.00001599329,0.001664569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.206984,"threshold_uncertainty_score":0.4618519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02983060857764487,"score_gpt":0.2850685848001583,"score_spread":0.2552379762225134,"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."}}