{"id":"W4406848857","doi":"10.1016/j.brs.2025.01.020","title":"Bayesian Optimization Of NeuroStimulation (BOONStim)","year":2025,"lang":"en","type":"letter","venue":"Brain stimulation","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Centre for Addiction and Mental Health Foundation; Canadian Institutes of Health Research; University of Toronto; BrainsWay; Indivior; Wellcome Trust; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; National Institutes of Health; Centre for Addiction and Mental Health; Brain and Behavior Research Foundation","keywords":"Neurostimulation; Bayesian probability; Computer science; Bayesian optimization; Neuroscience; Psychology; Artificial intelligence; Stimulation","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009405665,0.0007788044,0.0009150786,0.0003071352,0.0003441969,0.0008548212,0.0008066772,0.001737092,0.01053783],"category_scores_gemma":[0.003779205,0.0005333371,0.0004115975,0.0003567055,0.0007131396,0.0005685713,0.0009636726,0.001228519,0.001623442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061486,"about_ca_system_score_gemma":0.001435725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007580175,"about_ca_topic_score_gemma":0.008821739,"domain_scores_codex":[0.9995854,0.0001852313,0.00001283152,0.00007767024,0.00008926714,0.00004948754],"domain_scores_gemma":[0.9990973,0.0006654771,0.00005850117,0.00002885528,0.0001012687,0.00004857782],"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":[0.0003391732,0.00005576775,0.0006273975,0.0001755534,0.0001019381,0.0001366902,0.00004823858,0.8397321,0.001336976,0.04962769,0.01916126,0.08865707],"study_design_scores_gemma":[0.00004800663,0.00002962591,0.0001469846,0.00002504526,0.00001186896,0.00003160792,0.000006077697,0.9775336,0.0003190442,0.01759303,0.004244457,0.00001056193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006992129,0.001224984,0.969549,0.002819519,0.0002290083,0.0000927345,0.0002803522,0.0005933454,0.01821887],"genre_scores_gemma":[0.5879399,0.001371001,0.3794727,0.002199107,0.0004487183,0.0006491254,0.0007028224,0.0006471302,0.02656946],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01053783,"threshold_uncertainty_score":0.03525257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03580330700716212,"score_gpt":0.2773507719535238,"score_spread":0.2415474649463617,"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."}}