{"id":"W1977215610","doi":"10.1097/ccm.0b013e3182387d43","title":"A multicenter mortality prediction model for patients receiving prolonged mechanical ventilation*","year":2011,"lang":"en","type":"article","venue":"Critical Care Medicine","topic":"Respiratory Support and Mechanisms","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Nursing Research; National Heart, Lung, and Blood Institute","keywords":"Medicine; Mechanical ventilation; Logistic regression; Receiver operating characteristic; Confidence interval; Goodness of fit; Mortality rate; Area under the curve; Hemodialysis; Statistics; Emergency medicine; Internal medicine; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000306921,0.000185383,0.000367502,0.00009076094,0.0001059696,0.000005650327,0.00008052625,0.0001763602,0.0002852314],"category_scores_gemma":[0.001541849,0.0001451912,0.0001186575,0.00008917181,0.00013676,0.0001253511,0.00003366625,0.0001980773,0.000009600083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008426206,"about_ca_system_score_gemma":0.00007743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007472524,"about_ca_topic_score_gemma":0.00001009172,"domain_scores_codex":[0.9982882,0.00003565653,0.0004858604,0.0004002909,0.000439721,0.0003502612],"domain_scores_gemma":[0.9984117,0.00007230099,0.0000529392,0.0003257317,0.0007742338,0.0003631276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008206313,0.003950233,0.8562394,0.006225155,0.0003987821,0.0001688377,0.03108058,0.000005933975,0.0241804,0.01821216,0.006450358,0.04488186],"study_design_scores_gemma":[0.04052232,0.02365469,0.6647593,0.00276673,0.006545135,0.00004523511,0.01062414,0.1975184,0.0328925,0.01355252,0.005683161,0.001435864],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8451472,0.0001681367,0.1467132,0.0004979679,0.001643725,0.002388505,0.00008605525,0.0002518261,0.003103435],"genre_scores_gemma":[0.9922419,0.000003580472,0.005966844,0.0008421574,0.0003564542,0.0002071576,0.0002311574,0.00003548411,0.0001153085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1975125,"threshold_uncertainty_score":0.5920725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08822769346938542,"score_gpt":0.3473984915168246,"score_spread":0.2591707980474391,"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."}}