{"id":"W3207851532","doi":"10.1016/j.cjca.2021.07.155","title":"COVID-19 DIAGNOSIS BY POINT OF CARE LUNG ULTRASOUND: A NOVEL DEEP LEARNING ARTIFICIAL INTELLIGENCE METHOD","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Ultrasound in Clinical Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Burnaby Hospital","funders":"","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); Cohort; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Internal medicine; Population; Lung ultrasound; Lung; Intensive care medicine; Pathology; Disease; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.000792112,0.0001398084,0.0007761886,0.0001843314,0.0001281783,0.00001696003,0.0002022769,0.0002291935,0.0004216573],"category_scores_gemma":[0.01487976,0.0001354805,0.0003910556,0.0003543682,0.000285951,0.00004618817,0.00001582057,0.0007332095,0.000006993129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000512252,"about_ca_system_score_gemma":0.003806638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001195303,"about_ca_topic_score_gemma":0.003056828,"domain_scores_codex":[0.9980986,0.000290499,0.0008610713,0.0002438054,0.0001757421,0.0003302708],"domain_scores_gemma":[0.9937185,0.003436415,0.0003549827,0.0002748697,0.0008096122,0.001405617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004947465,0.0001500451,0.6755151,0.0008836733,0.003538911,0.001022948,0.01369169,0.05627663,0.104774,0.01903611,0.03432171,0.0902945],"study_design_scores_gemma":[0.001359518,0.001658335,0.01546496,0.0002466718,0.001842795,0.01154622,0.02568324,0.0002395579,0.02220619,0.007479068,0.9116214,0.0006520804],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04687247,0.005927645,0.9367765,0.007142071,0.0005138338,0.000237082,0.0001760459,0.00001234456,0.002342052],"genre_scores_gemma":[0.9769933,0.0004461177,0.02043718,0.001421116,0.0005587104,0.00001674161,0.00006580867,0.00002229982,0.00003870655],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9301208,"threshold_uncertainty_score":0.9934183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04801946652369529,"score_gpt":0.3708803688114347,"score_spread":0.3228609022877394,"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."}}