{"id":"W1745273410","doi":"10.3233/ica-2010-0344","title":"A multi-criteria optimization framework for industrial shop scheduling using fuzzy set theory","year":2010,"lang":"en","type":"article","venue":"Integrated Computer-Aided Engineering","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Computer science; Mathematical optimization; Fuzzy logic; Fuzzy set; Scheduling (production processes); Industrial engineering; Mathematics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004389857,0.0004681932,0.0004050686,0.0003879947,0.0001327752,0.0003019506,0.0003505884,0.0005905411,0.0000644329],"category_scores_gemma":[0.0004164607,0.0005035783,0.0001532047,0.0006474638,0.00003176728,0.0003019588,0.00004989056,0.00111193,0.000007888604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001107413,"about_ca_system_score_gemma":0.00006047731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008016533,"about_ca_topic_score_gemma":0.000001457218,"domain_scores_codex":[0.9982802,0.00003440386,0.0005584185,0.0004020742,0.0001714724,0.0005534318],"domain_scores_gemma":[0.9987636,0.0003611394,0.00007527216,0.000379887,0.0002160967,0.00020405],"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":[0.00001920983,0.00002363869,0.00001513745,0.00004296532,0.0001041315,0.000004452283,0.0002278567,0.9869863,0.007433104,0.001254543,0.00002223408,0.003866378],"study_design_scores_gemma":[0.0009407421,0.00003444207,0.000004401376,0.0002557326,0.00004586989,0.00002847454,0.00008520076,0.9937377,0.003993648,0.0001753302,0.000143677,0.000554766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06812178,0.00007329569,0.923187,0.00001808272,0.006525502,0.0003912573,0.00004393217,0.00162524,0.00001395308],"genre_scores_gemma":[0.132888,0.000007938483,0.8654864,0.00003262658,0.001243273,0.00004821996,0.0001259844,0.0001601732,0.000007326578],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06476625,"threshold_uncertainty_score":0.9997416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03596246882074433,"score_gpt":0.2718421789509948,"score_spread":0.2358797101302504,"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."}}