{"id":"W3120525931","doi":"10.1007/s10140-020-01875-1","title":"Learning from pathophysiological aspects of COVID-19 clinical, laboratory, and high-resolution CT features: a retrospective analysis of 128 cases by disease severity","year":2021,"lang":"en","type":"article","venue":"Emergency Radiology","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Medicine; myalgia; Internal medicine; Sore throat; Coronavirus disease 2019 (COVID-19); Disease; Pneumonia; Pathophysiology; Severity of illness; Gastroenterology; High-resolution computed tomography; Retrospective cohort study; Radiology; Lung; Surgery; Infectious disease (medical specialty)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.000844505,0.0002121259,0.001526783,0.0001518824,0.0001369305,0.000002913981,0.0001228469,0.0001677098,0.0008428616],"category_scores_gemma":[0.1390507,0.000174329,0.0004273526,0.001162162,0.0008303946,0.00003993448,0.0002414034,0.0006185265,0.000002625282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001399937,"about_ca_system_score_gemma":0.0007014482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001092922,"about_ca_topic_score_gemma":0.0001638448,"domain_scores_codex":[0.9960035,0.001591592,0.0008930491,0.0008423841,0.0003412797,0.0003281778],"domain_scores_gemma":[0.9924076,0.005737126,0.0003832057,0.0005016032,0.0003992321,0.0005711962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001215662,0.0006799414,0.9749064,0.0001984484,0.002932991,0.0006565182,0.0002018578,0.0002059887,0.01145363,0.0002583865,0.006899065,0.0003910691],"study_design_scores_gemma":[0.001059692,0.001125353,0.9916347,0.0000207529,0.001630321,0.00000185362,0.0001783183,0.0009276014,0.0001503854,0.001725148,0.001394791,0.0001510935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898005,0.005084284,0.0003754558,0.00343259,0.0001973887,0.0002245064,0.0008177977,0.00004074102,0.00002677612],"genre_scores_gemma":[0.9803597,0.01826979,0.0001548068,0.0004952312,0.0001554909,0.00002216567,0.000427264,0.00001171909,0.0001038667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1382062,"threshold_uncertainty_score":0.9228743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04273691289174202,"score_gpt":0.4082346167704802,"score_spread":0.3654977038787382,"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."}}