{"id":"W2789522810","doi":"10.1097/pcc.0000000000001460","title":"Creating a High-Frequency Electronic Database in the PICU: The Perpetual Patient*","year":2018,"lang":"en","type":"article","venue":"Pediatric Critical Care Medicine","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Medicine; Interquartile range; Database; Prospective cohort study; Electronic medical record; Medical record; Emergency medicine; Medical emergency; Internal medicine; Computer science","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":[0.0008145069,0.0002156118,0.0003306858,0.0002056108,0.0003804644,0.00001016498,0.0003099934,0.0001720347,0.0002383244],"category_scores_gemma":[0.006027441,0.0001129072,0.00005140612,0.0009490679,0.0006517826,0.00007273796,0.00007779618,0.001236912,0.00004962409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001719617,"about_ca_system_score_gemma":0.0002749725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001123285,"about_ca_topic_score_gemma":0.0002270172,"domain_scores_codex":[0.9974023,0.0002623731,0.0005178008,0.0003901091,0.0006552109,0.0007721804],"domain_scores_gemma":[0.9971511,0.001588734,0.00005767856,0.0006971942,0.0003562756,0.0001490116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003867691,0.0004820766,0.8011654,0.001344653,0.00003742317,0.0009245659,0.0517749,3.005754e-7,0.0003538809,0.07144319,0.004655232,0.06743158],"study_design_scores_gemma":[0.01863103,0.06297615,0.5039859,0.002944323,0.004897368,0.003336985,0.356003,0.0003297021,0.001562096,0.01458318,0.02812975,0.002620495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9624802,0.007561543,0.0001292479,0.02554076,0.0007573363,0.0006047371,0.00001343994,0.0001177456,0.002794923],"genre_scores_gemma":[0.9917744,0.000275857,0.0002153957,0.002617546,0.004927992,0.00009698334,0.00005844367,0.00002144234,0.00001191778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.304228,"threshold_uncertainty_score":0.7215845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02670608630875778,"score_gpt":0.3537826418346469,"score_spread":0.3270765555258891,"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."}}