{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009929395,0.001550997,0.0009463292,0.003552999,0.0006422146,0.001144089,0.00216663,0.001518653,0.008963859],"category_scores_gemma":[0.005574385,0.0003741388,0.0007742255,0.002827496,0.0004542925,0.0006108481,0.001364158,0.0009333476,0.009926184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001339931,"about_ca_system_score_gemma":0.002282361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02292852,"about_ca_topic_score_gemma":0.0339954,"domain_scores_codex":[0.9990559,0.0001555105,0.0001804347,0.0002437366,0.0002736863,0.00009072265],"domain_scores_gemma":[0.9982712,0.0004602321,0.0002359565,0.0003713327,0.0005050794,0.0001561532],"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":[0.001226994,0.0004734232,0.02674191,0.004036,0.0002143145,0.00156534,0.0003433928,0.002455669,0.006780045,0.002058849,0.8700411,0.08406309],"study_design_scores_gemma":[0.0007726349,0.0002806088,0.1045878,0.001370869,0.0002735476,0.003979802,0.0007296578,0.01304228,0.008011466,0.003234066,0.863562,0.0001551191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02249127,0.002241626,0.003148385,0.0008337203,0.0001652921,0.0004025541,0.9618502,0.00325195,0.005615076],"genre_scores_gemma":[0.01755238,0.0005917086,0.004497832,0.0001730272,0.00005587024,0.0003641561,0.9755809,0.0001059454,0.001078126],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02292852,"threshold_uncertainty_score":0.0455901,"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."}}