{"id":"W4291021452","doi":"10.1038/s41597-022-01608-8","title":"BRAX, Brazilian labeled chest x-ray dataset","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"National Institutes of Health; Sociedade Beneficente Israelita Brasileira Albert Einstein; National Institute of Biomedical Imaging and Bioengineering; U.S. Department of Health and Human Services","keywords":"Computer science; Radiology; Radiography; Medical physics; Artificial intelligence; Medicine","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":["insufficient_payload"],"category_scores_codex":[0.002390236,0.0001528407,0.0002377284,0.0002637983,0.0008282661,0.0002593473,0.001927722,0.00003123818,0.007163635],"category_scores_gemma":[0.0008508727,0.0001534547,0.00003756868,0.001215466,0.00030139,0.0003426881,0.003667048,0.0003355273,0.0009106054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367844,"about_ca_system_score_gemma":0.0006017714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001992729,"about_ca_topic_score_gemma":0.0001340374,"domain_scores_codex":[0.9969333,0.0001077337,0.0002865516,0.001293954,0.0009565137,0.0004218909],"domain_scores_gemma":[0.9938339,0.0001655896,0.00009523114,0.005618108,0.00005545434,0.0002316915],"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":[0.00002791867,0.0003802189,0.0007035931,0.00005510959,0.00002568242,0.00009788945,0.0001117368,0.00002054141,0.006289721,0.00003153761,0.9881604,0.004095696],"study_design_scores_gemma":[0.0008569492,0.00006059546,0.00257241,0.00002770641,0.00009072221,0.00002896672,0.0001478637,0.00166547,0.0004575164,0.00002935304,0.993899,0.0001633767],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1038113,0.001163496,0.0001976864,0.2036606,0.01393691,0.002415353,0.6728041,0.0008280163,0.001182528],"genre_scores_gemma":[0.1775566,0.00001351559,0.003140553,0.03941664,0.0004156166,0.00009375643,0.7617348,0.00008596313,0.01754258],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.164244,"threshold_uncertainty_score":0.9998673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08167703993095068,"score_gpt":0.361811452426393,"score_spread":0.2801344124954424,"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."}}