{"id":"W2616133052","doi":"10.5267/j.uscm.2017.4.002","title":"Performance evaluation of a GRASP-based approach for stochastic scheduling problems","year":2017,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"GRASP; Computer science; Scheduling (production processes); Mathematical optimization; Operations research; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001297728,0.0001797347,0.0001908194,0.0001750012,0.0002455847,0.0000794456,0.0003559246,0.00006049547,0.00002457989],"category_scores_gemma":[0.00007439667,0.0001827964,0.00007155108,0.0001012634,0.00005229158,0.0001176227,0.00003690241,0.00007590405,0.000003319061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001159564,"about_ca_system_score_gemma":0.00002576106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008577464,"about_ca_topic_score_gemma":0.000001977633,"domain_scores_codex":[0.9987082,0.0000253033,0.0002863728,0.0002487931,0.0004594008,0.0002718614],"domain_scores_gemma":[0.9990554,0.00003341382,0.0001255323,0.0005406069,0.0001927002,0.00005231954],"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":[0.00001267089,0.00004097001,0.0002289016,0.0004731082,0.00006595164,1.466743e-7,0.0001292359,0.9744344,0.00002279228,0.0002705498,0.00003980154,0.02428145],"study_design_scores_gemma":[0.001713193,0.00004129723,0.0005138748,0.0001288692,0.0001183113,2.424825e-7,0.0002033148,0.9967163,0.0001985718,0.0001188573,0.00004396931,0.0002031803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.022443,0.0001271698,0.9725794,0.00007616048,0.0002669299,0.001620476,0.00001174665,0.0001418523,0.002733245],"genre_scores_gemma":[0.746578,0.00001217376,0.2525132,0.00001534359,0.00005470365,0.0006215216,0.00008944617,0.00003094984,0.00008469306],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.724135,"threshold_uncertainty_score":0.7454221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03467342728039374,"score_gpt":0.2654567775908657,"score_spread":0.2307833503104719,"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."}}