{"id":"W2767803078","doi":"10.1017/cjn.2017.240","title":"Robotic-Assisted and Image-Guided MRI-Compatible Stereoelectroencephalography","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Epilepsiatutkimussäätiö; Montreal Neurological Institute and Hospital; Japan Epilepsy Research Foundation; Osaka Medical Research Foundation for Intractable Diseases; Uehara Memorial Foundation","keywords":"Stereoelectroencephalography; Medicine; Neuronavigation; Radiology; Intraoperative MRI; Stereotaxy; Magnetic resonance imaging; Asymptomatic; Surgery; Epilepsy; Epilepsy surgery; Interventional magnetic resonance imaging; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.0006637534,0.0003034837,0.0001817939,0.0005978027,0.0001146886,0.0002952649,0.0004131721,0.0002432454,0.001000811],"category_scores_gemma":[0.001792474,0.00008998936,0.00032255,0.0002284167,0.0004364912,0.0003559121,0.0002980266,0.000253061,0.000299664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001581757,"about_ca_system_score_gemma":0.0003537131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002759929,"about_ca_topic_score_gemma":0.0005664015,"domain_scores_codex":[0.9995645,0.0001254609,0.00005531754,0.00008213836,0.0001192162,0.00005347007],"domain_scores_gemma":[0.9990108,0.000332031,0.0003529671,0.0001522882,0.00007553703,0.00007633406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001297684,0.0003646013,0.2976812,0.0007139529,0.0004003161,0.01914325,0.0004726673,0.002881376,0.07882644,0.0012861,0.001995719,0.5949367],"study_design_scores_gemma":[0.0002796105,0.005400491,0.3879808,0.000192036,0.0003521624,0.5387385,0.0002755599,0.007253629,0.04288661,0.0009084187,0.01561815,0.0001139921],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9327983,0.006612915,0.05405819,0.0002690134,0.00007445757,0.0001009683,0.0001831311,0.0002046411,0.005698401],"genre_scores_gemma":[0.979201,0.001707498,0.01809485,0.000125252,0.0001297624,0.0000409212,0.0001466051,0.00002105503,0.0005329407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001000811,"threshold_uncertainty_score":0.003510356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05994174822161724,"score_gpt":0.3276024068217495,"score_spread":0.2676606586001322,"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."}}