{"id":"W1996161633","doi":"10.1097/00002480-200607000-00044","title":"ACCURACY OF HEMODYNAMIC MONITORING USING TRANSPULMONARY THERMODILUTION DURING TOTAL LIQUID VENTILATION (TLV)","year":2006,"lang":"en","type":"article","venue":"ASAIO Journal","topic":"Respiratory Support and Mechanisms","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Medicine; Hemodynamics; Anesthesia; Transpulmonary pressure; Cardiac output; Vascular resistance; Central venous pressure; Stroke volume; Positive end-expiratory pressure; Tidal volume; Pulmonary artery catheter; Cardiac index; Pulmonary artery; Mean arterial pressure; Ventilation (architecture); Arterial blood; Blood volume; Mechanical ventilation; Cardiology; Blood pressure; Internal medicine; Lung; Heart rate; Lung volumes; Respiratory system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001926192,0.0001163705,0.0001984388,0.0001581518,0.0001462399,0.00001650058,0.00005109224,0.00008444997,0.00008642527],"category_scores_gemma":[0.00001138947,0.0001067486,0.0001620188,0.0001148084,0.00002174139,0.0002906224,0.00001016609,0.0002422026,0.000003440627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001240017,"about_ca_system_score_gemma":0.0001126311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002279788,"about_ca_topic_score_gemma":7.361053e-7,"domain_scores_codex":[0.9989217,0.00002737514,0.0004112719,0.0001175511,0.0003086936,0.0002134444],"domain_scores_gemma":[0.9994338,0.00001261376,0.0002495264,0.0001206116,0.0001006347,0.0000828484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005227978,0.00008706348,0.01565479,0.00005130687,0.00002538041,0.0001330673,0.00007113633,0.000828909,0.9793999,0.00002282618,0.000002309356,0.003200572],"study_design_scores_gemma":[0.001526943,0.0003628802,0.2990259,0.0004245363,0.0001461941,0.002600063,0.0001580097,0.001309739,0.6940144,0.0001661578,0.0001061936,0.0001589036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927426,0.0005059,0.005791176,0.00002698458,0.0004487228,0.00009181242,0.000001812686,0.00002294572,0.0003680653],"genre_scores_gemma":[0.9977924,0.00002518159,0.001181215,0.000005835786,0.000828161,0.000001416794,0.000006047759,0.0000229738,0.0001367905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2853854,"threshold_uncertainty_score":0.4353081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01777433639470172,"score_gpt":0.2756128314239292,"score_spread":0.2578384950292275,"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."}}