{"id":"W3002703537","doi":"10.1007/s40140-020-00368-8","title":"Preprocedural Assessment for Patients Anticipating Sedation","year":2020,"lang":"en","type":"article","venue":"Current anesthesiology reports","topic":"Anesthesia and Sedative Agents","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Sedation; Medicine; Anesthesiology; Multidisciplinary approach; Intensive care medicine; Quality (philosophy); Risk assessment; Medical emergency; Anesthesia; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003086342,0.0003747168,0.0003897666,0.001030391,0.0007315972,0.0007782021,0.0003243088,0.0007979407,0.003014184],"category_scores_gemma":[0.003056748,0.0001309377,0.000370212,0.0003409892,0.0001454252,0.0006514896,0.0003346277,0.001515076,0.0005061021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002659446,"about_ca_system_score_gemma":0.001131078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001201079,"about_ca_topic_score_gemma":0.003638347,"domain_scores_codex":[0.9998083,0.00003447049,0.00004455608,0.00001762321,0.00003993548,0.00005511516],"domain_scores_gemma":[0.9988757,0.0003480724,0.0001970008,0.0000286744,0.0002139277,0.0003366832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001403788,0.0007471163,0.7875879,0.0005592676,0.00007516921,0.03381009,0.0008502842,0.0004021857,0.006360429,0.0007251853,0.01187411,0.1556045],"study_design_scores_gemma":[0.0001542597,0.003284863,0.8611889,0.002706923,0.0004115992,0.08073319,0.004718359,0.003940235,0.008075424,0.003257086,0.03137569,0.0001535649],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9271324,0.01737046,0.00595434,0.01307412,0.001141309,0.0004533946,0.000568348,0.0002063786,0.03409926],"genre_scores_gemma":[0.9803281,0.006572973,0.007548863,0.002058837,0.0009507402,0.0001438222,0.0005852301,0.0000194397,0.001791969],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003014184,"threshold_uncertainty_score":0.01008344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.061324536662129,"score_gpt":0.3598313363543126,"score_spread":0.2985067996921836,"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."}}