{"id":"W2087393302","doi":"10.1111/j.1467-8640.2005.00278.x","title":"APPLYING MACHINE LEARNING TO LOW-KNOWLEDGE CONTROL OF OPTIMIZATION ALGORITHMS","year":2005,"lang":"en","type":"article","venue":"Computational Intelligence","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Irish Research Council; Science Foundation Ireland","keywords":"Computer science; Machine learning; Domain knowledge; Algorithm; Artificial intelligence; Control (management); Set (abstract data type); Optimization algorithm; Scheduling (production processes); Mathematical optimization; Mathematics","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":[0.000162923,0.000134273,0.000162189,0.0001748874,0.0000691254,0.00002893953,0.0001521996,0.00005210752,0.0001496517],"category_scores_gemma":[0.0001075817,0.0001497509,0.00004648065,0.0003956691,0.00002555755,0.000109617,0.00002109666,0.0001429812,0.0001386694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005836579,"about_ca_system_score_gemma":0.00002381762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002766836,"about_ca_topic_score_gemma":0.000001329884,"domain_scores_codex":[0.9991186,0.00002680536,0.0003547259,0.0001642253,0.0001764323,0.0001591797],"domain_scores_gemma":[0.9992562,0.0001884615,0.00004796797,0.00008338904,0.0003301993,0.00009376949],"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":[0.000004970265,0.00002647106,0.00003980549,0.00001963243,0.00001854272,3.604419e-7,0.0003627842,0.9251245,0.00003427809,0.0003475004,0.00001860897,0.0740026],"study_design_scores_gemma":[0.0001269584,0.0000240295,0.00002299655,0.00004125373,0.000007470315,0.000003841767,0.00005764913,0.9973548,0.00158558,0.00007974034,0.0005414417,0.0001542598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006209782,0.0005920987,0.9973856,0.00007010338,0.0001988979,0.0002437507,0.000008286212,0.0002371814,0.0006431633],"genre_scores_gemma":[0.5590617,0.00002103797,0.4405839,0.00008347938,0.00009775974,0.00003899682,0.00003429924,0.00002061954,0.00005814178],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5584407,"threshold_uncertainty_score":0.6106666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517091568407795,"score_gpt":0.2613674780904295,"score_spread":0.2461965624063516,"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."}}