{"id":"W2192203593","doi":"10.1109/jproc.2015.2494218","title":"Taking the Human Out of the Loop: A Review of Bayesian Optimization","year":2015,"lang":"en","type":"review","venue":"Proceedings of the IEEE","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":5868,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of British Columbia","funders":"","keywords":"Bayesian optimization; Loop (graph theory); Bayesian probability; Human-in-the-loop; Computer science; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002967358,0.001261882,0.001942474,0.002567687,0.0005110762,0.002180117,0.00167849,0.002072366,0.003535488],"category_scores_gemma":[0.007534511,0.0006432518,0.0008398872,0.004857996,0.001746293,0.00268935,0.0009331733,0.002082363,0.001867485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001730642,"about_ca_system_score_gemma":0.003297863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005024743,"about_ca_topic_score_gemma":0.005790241,"domain_scores_codex":[0.9987852,0.0004425001,0.0001239195,0.0001805149,0.0004145407,0.00005326462],"domain_scores_gemma":[0.9946561,0.00419041,0.0002357587,0.0001089386,0.000711973,0.00009681055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005894478,0.00009953,0.0006638317,0.01271232,0.0001766701,0.0001049832,0.0001473682,0.008060265,0.0003140194,0.09130342,0.03700556,0.8493531],"study_design_scores_gemma":[0.00003114086,0.0001498794,0.001619144,0.01185276,0.0002398957,0.0006263572,0.0002276969,0.006925553,0.0006901898,0.1154576,0.8620602,0.0001194136],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002337059,0.9822565,0.01080326,0.002335164,0.0002547638,0.000009733281,0.00003359842,0.00001992009,0.004053332],"genre_scores_gemma":[0.004164895,0.988736,0.005193294,0.00051817,0.0005973272,0.0000196829,0.00004214359,0.00001403222,0.0007145717],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005024743,"threshold_uncertainty_score":0.01569307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2723421006942705,"score_gpt":0.4942171047619189,"score_spread":0.2218750040676484,"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."}}