{"id":"W2921012149","doi":"10.1097/ccm.0000000000003678","title":"Predicting Fluid Responsiveness: Time for Automation*","year":2019,"lang":"en","type":"letter","venue":"Critical Care Medicine","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Surgical Specialties (Canada)","funders":"","keywords":"Medicine; Agricultural science; Operations management; Management; Engineering; Economics; Biology","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":[0.002542367,0.0004904357,0.0007892641,0.001126423,0.0008482105,0.003111439,0.0008678702,0.002586532,0.007611627],"category_scores_gemma":[0.03473133,0.0003282383,0.0005899497,0.0007521141,0.0006746999,0.002306596,0.0007697564,0.00642147,0.006379105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389874,"about_ca_system_score_gemma":0.001600249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002649781,"about_ca_topic_score_gemma":0.003607344,"domain_scores_codex":[0.9971448,0.001230617,0.0005041877,0.0003096488,0.0006545446,0.0001562444],"domain_scores_gemma":[0.979852,0.01411916,0.001007914,0.0007865874,0.003230616,0.001003656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007430789,0.0001294175,0.04448975,0.0002214669,0.0000482574,0.005005941,0.0003651671,0.001378074,0.001165729,0.003023181,0.5894842,0.3539457],"study_design_scores_gemma":[0.0004766973,0.0009561696,0.0793142,0.004138415,0.0002493043,0.04514339,0.002333818,0.05588255,0.004761385,0.08180021,0.7245517,0.0003922073],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01766729,0.0109053,0.008928647,0.9163812,0.01474622,0.0001410655,0.0004275414,0.0006971729,0.03010555],"genre_scores_gemma":[0.5535786,0.02536871,0.0512434,0.2752228,0.06623367,0.0005143944,0.001284635,0.0006471714,0.02590664],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.007611627,"threshold_uncertainty_score":0.02546346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0227075566471053,"score_gpt":0.3386864253952432,"score_spread":0.3159788687481379,"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."}}