{"id":"W3183653886","doi":"10.1016/s2213-2600(21)00157-0","title":"Advancing precision medicine for acute respiratory distress syndrome","year":2021,"lang":"en","type":"article","venue":"The Lancet Respiratory Medicine","topic":"Respiratory Support and Mechanisms","field":"Medicine","cited_by":192,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Innovate UK; Medical Research Council; U.S. Food and Drug Administration; U.S. Department of Health and Human Services; National Institutes of Health; Queen's University; Queen's University Belfast; Marcus Foundation; National Heart, Lung, and Blood Institute; Government of South Australia; National Institute for Health and Care Research; U.S. Department of Veterans Affairs; Wellcome Trust; U.S. Department of Defense","keywords":"Precision medicine; ARDS; Pandemic; Clinical trial; MEDLINE; Acute respiratory distress; Multidisciplinary approach","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00316057,0.0006120423,0.001989052,0.0002649794,0.0004756754,0.0000260281,0.0006090873,0.0002983233,0.001377613],"category_scores_gemma":[0.002051467,0.0003646981,0.000266595,0.0008440551,0.0006637299,0.0002096723,0.0001962319,0.000758777,0.00007059312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001999744,"about_ca_system_score_gemma":0.0005079318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001074567,"about_ca_topic_score_gemma":0.00003377667,"domain_scores_codex":[0.9950435,0.0003345433,0.001249317,0.0009962394,0.001229113,0.001147311],"domain_scores_gemma":[0.9951852,0.0007568279,0.0004455814,0.002208845,0.0007516339,0.0006518937],"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":[0.002686215,0.0002831034,0.007258706,0.0009569682,0.00105454,0.004738183,0.00116689,0.00001392896,0.4632581,0.005852646,0.4680435,0.04468722],"study_design_scores_gemma":[0.01101715,0.003706722,0.009693372,0.001608261,0.001264001,0.0008527645,0.001007555,0.00004868731,0.02110018,0.001565595,0.9476776,0.0004581757],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8171057,0.04024206,0.01798107,0.08049048,0.007053177,0.005981613,0.0003098135,0.001169409,0.02966663],"genre_scores_gemma":[0.7776141,0.001692908,0.0042356,0.1645721,0.03065871,0.001543217,0.0007780686,0.0006878171,0.01821744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.479634,"threshold_uncertainty_score":0.9998805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06129139808331863,"score_gpt":0.368456160425284,"score_spread":0.3071647623419653,"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."}}