{"id":"W3120506007","doi":"10.1148/radiol.2021203957","title":"The RSNA International COVID-19 Open Radiology Database (RICORD)","year":2021,"lang":"en","type":"article","venue":"Radiology","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":139,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Toronto","funders":"National Institutes of Health; National Science Foundation","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); Radiology; Generalizability theory; Medical imaging; Medical physics; Radiography; Database; Pathology; Infectious disease (medical specialty); Disease; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008577411,0.0001776691,0.0004378719,0.0000988129,0.0002786866,0.00006362011,0.0007924958,0.0001643691,0.001382241],"category_scores_gemma":[0.007971505,0.0001342225,0.0001065986,0.0002469852,0.0003709649,0.00008763775,0.0007239255,0.0003689273,0.0001921608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005392665,"about_ca_system_score_gemma":0.00177837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003030787,"about_ca_topic_score_gemma":0.0002481337,"domain_scores_codex":[0.9979684,0.0004648153,0.000375737,0.0006074283,0.0001651456,0.0004184654],"domain_scores_gemma":[0.9954605,0.003022627,0.0001272611,0.0009281692,0.0001510483,0.0003104295],"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":[0.0004844761,0.0002312208,0.02512546,0.00004219896,0.0003821687,0.002075134,0.0002392347,0.0001046887,0.005843324,0.02142307,0.9383956,0.005653385],"study_design_scores_gemma":[0.002381159,0.0001444912,0.006561684,0.00001928229,0.00007465317,0.005142028,0.0001187077,0.0004756045,0.0003970329,0.0009503235,0.9835923,0.0001426757],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.05107893,0.004585444,0.005044094,0.9264991,0.005273415,0.0009313485,0.0001538541,0.0002030266,0.006230783],"genre_scores_gemma":[0.3097431,0.006446552,0.006209648,0.6597084,0.0028609,0.0004004015,0.002027555,0.0001043075,0.0124991],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2667907,"threshold_uncertainty_score":0.9995306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06861568055788676,"score_gpt":0.4014884995381514,"score_spread":0.3328728189802646,"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."}}