{"id":"W1495880578","doi":"10.1007/978-3-540-75757-3_59","title":"Automatic Target and Trajectory Identification for Deep Brain Stimulation (DBS) Procedures","year":2007,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research","keywords":"Deep brain stimulation; Subthalamic nucleus; Trajectory; Probabilistic logic; Computer science; Surgical planning; Neurosurgery; Visualization; Artificial intelligence; Medicine; Surgery; Parkinson's disease; Pathology; Physics","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":[0.000329308,0.0004754403,0.0003361669,0.0004314787,0.000347646,0.0005073395,0.0003512028,0.0006557041,0.002615595],"category_scores_gemma":[0.001390806,0.0002725722,0.0002710458,0.0003644971,0.0002179717,0.0004230048,0.0004640456,0.0005449779,0.0008017374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002430699,"about_ca_system_score_gemma":0.0008250047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001794575,"about_ca_topic_score_gemma":0.003243652,"domain_scores_codex":[0.9997104,0.00008536276,0.00002076033,0.00004079447,0.0001153585,0.00002739368],"domain_scores_gemma":[0.9995416,0.0002385793,0.00004893829,0.00004319185,0.0001040686,0.00002361429],"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":[0.001083263,0.0000640735,0.001589828,0.0001819632,0.00003682225,0.0001521421,0.0001119882,0.03467128,0.2033548,0.004042553,0.002203565,0.7525078],"study_design_scores_gemma":[0.00007219626,0.0003014651,0.007882188,0.00003248039,0.00003879616,0.001070122,0.00007949355,0.8506638,0.1264791,0.009473464,0.003858897,0.00004807341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02539935,0.0002393507,0.972271,0.00009228585,0.00002606147,0.00004156342,0.0001056493,0.0008045267,0.001020253],"genre_scores_gemma":[0.5576354,0.0003181779,0.4391541,0.00007718805,0.00002519492,0.0000952195,0.0002882746,0.0001623245,0.002244121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002615595,"threshold_uncertainty_score":0.008750081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01497246390705853,"score_gpt":0.2966107171359505,"score_spread":0.281638253228892,"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."}}