{"id":"W4387801231","doi":"10.1007/s11701-023-01722-8","title":"Surgical skill level classification model development using EEG and eye-gaze data and machine learning algorithms","year":2023,"lang":"en","type":"article","venue":"Journal of Robotic Surgery","topic":"Traumatic Brain Injury and Neurovascular Disturbances","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute; National Institutes of Health; Roswell Park Cancer Institute","keywords":"Gaze; Artificial intelligence; Random forest; Medicine; Dissection (medical); Eye tracking; Machine learning; Electroencephalography; Computer science; Surgery","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":[0.001801401,0.0001327184,0.0004689939,0.0002431377,0.0001323056,0.00003769144,0.00008436556,0.00006579655,0.000008397271],"category_scores_gemma":[0.0005022925,0.0001033875,0.00007180052,0.0002269179,0.00007311408,0.0002205546,0.00009250325,0.0003037828,0.000002390472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003016075,"about_ca_system_score_gemma":0.0002066384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002951052,"about_ca_topic_score_gemma":9.664096e-7,"domain_scores_codex":[0.9985157,0.0001002596,0.000583653,0.0002187969,0.0003891009,0.0001924463],"domain_scores_gemma":[0.9986746,0.0005938486,0.0002915575,0.0001965866,0.00008307583,0.0001603661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007285867,0.0006292714,0.44484,0.001310696,0.001486924,0.002455191,0.00307457,0.02664462,0.005081449,0.0001166663,0.004568895,0.5090631],"study_design_scores_gemma":[0.0007714758,0.00004030814,0.3761138,0.0004945929,0.0001993994,0.001879563,0.0002560132,0.6182784,0.000118801,0.00004672244,0.001638578,0.0001623751],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809021,0.001865252,0.01592002,0.0008741404,0.0002941473,0.00008238327,0.000004992658,0.00002739885,0.0000295282],"genre_scores_gemma":[0.9831715,0.001502217,0.01476095,0.00006520862,0.0001195619,0.00000101077,0.00004386626,0.00002230713,0.0003133944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5916338,"threshold_uncertainty_score":0.4216019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2588868175223979,"score_gpt":0.3471521103484501,"score_spread":0.08826529282605222,"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."}}