{"id":"W3123661268","doi":"10.1148/ryai.2021200254","title":"The RSNA Pulmonary Embolism CT Dataset","year":2021,"lang":"en","type":"article","venue":"Radiology Artificial Intelligence","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Pulmonary embolism; Nuclear medicine; Radiology; Internal 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":[],"category_scores_codex":[0.0004698474,0.0001729912,0.0003905352,0.00004956608,0.0004201774,0.00004780901,0.0002529666,0.0000674462,0.0009082038],"category_scores_gemma":[0.0003654628,0.0001264949,0.0001114494,0.0002558685,0.0003576494,0.00006058587,0.0001696213,0.000278167,0.00108253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004860434,"about_ca_system_score_gemma":0.0001296732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005809251,"about_ca_topic_score_gemma":0.00008993676,"domain_scores_codex":[0.9983102,0.0001562679,0.0004426298,0.0004435391,0.0001801754,0.0004672005],"domain_scores_gemma":[0.9985915,0.0003352613,0.00008090951,0.0007601143,0.00009621606,0.0001359918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001457657,0.001057727,0.000820415,0.00006357775,0.0004290496,0.004230287,0.0002835738,0.000194691,0.007237135,0.3948969,0.1357295,0.4549114],"study_design_scores_gemma":[0.00006898039,0.0002292017,0.01242849,0.00006163744,0.0003089735,0.00243673,0.001552415,0.002380687,0.03971126,0.02943468,0.9110093,0.0003777005],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.670581,0.03835997,0.02993602,0.1646156,0.01444275,0.003764748,0.0009571007,0.0007661106,0.07657662],"genre_scores_gemma":[0.9882118,0.004763511,0.0004060793,0.004134955,0.0007187214,0.00007732432,0.0005510949,0.00002682014,0.001109675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7752798,"threshold_uncertainty_score":0.9996952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04509334302498019,"score_gpt":0.324612038351644,"score_spread":0.2795186953266638,"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."}}