{"id":"W2894053729","doi":"10.1007/s00701-018-3687-5","title":"Optimal cerebral perfusion pressure via transcranial Doppler in TBI: application of robotic technology","year":2018,"lang":"en","type":"article","venue":"Acta Neurochirurgica","topic":"Traumatic Brain Injury and Neurovascular Disturbances","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"Cambridge Commonwealth Trust; University of Cambridge; University of Manitoba","keywords":"Transcranial Doppler; Medicine; Cerebral perfusion pressure; Intracranial pressure; Traumatic brain injury; Cerebral autoregulation; Neuroradiology; Anesthesia; Autoregulation; Perfusion; Neurology; Neurosurgery; Internal medicine; Cerebral blood flow; Blood pressure; Surgery","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":[0.0006548635,0.0004080138,0.0004320228,0.0005978859,0.0002061055,0.0006300135,0.0004132162,0.0004262774,0.0005577886],"category_scores_gemma":[0.002061606,0.0001844886,0.0002705279,0.000354235,0.0007732891,0.0006854149,0.0005972289,0.000404684,0.0001362364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003567597,"about_ca_system_score_gemma":0.0006190652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008191948,"about_ca_topic_score_gemma":0.000806964,"domain_scores_codex":[0.9996252,0.0001480039,0.00002987078,0.00006653707,0.00007892826,0.00005145501],"domain_scores_gemma":[0.9996836,0.0001253223,0.00008692701,0.00004244025,0.00004066753,0.00002107346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003830591,0.0005951077,0.03869496,0.001776364,0.0001529674,0.002763268,0.0007769261,0.01508364,0.3679846,0.001956768,0.001564327,0.5648204],"study_design_scores_gemma":[0.0005121281,0.02732747,0.2963982,0.0007405117,0.001255566,0.05304365,0.001924282,0.1294695,0.4525262,0.008751063,0.02744602,0.000605516],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8715531,0.02584485,0.09726065,0.0007488909,0.000152527,0.0002229102,0.0001086029,0.0003244192,0.003784079],"genre_scores_gemma":[0.9747065,0.005246185,0.01953662,0.0001086931,0.000122404,0.00007217889,0.00003211939,0.00001481566,0.0001606095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008191948,"threshold_uncertainty_score":0.003463268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00988660562748237,"score_gpt":0.2495926345597906,"score_spread":0.2397060289323082,"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."}}