{"id":"W2547714726","doi":"10.1161/circimaging.116.005718","title":"Developing a Deeper Understanding of Sex Differences in the Diagnostic Performance of Computed Tomographic Perfusion Imaging Toward a More Personalized Approach","year":2016,"lang":"en","type":"letter","venue":"Circulation Cardiovascular Imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Computed tomographic; Computed tomography; Radiology; Perfusion scanning; Perfusion; Tomographic reconstruction; Computed tomographic angiography; Tomography; Medical physics; Angiography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00149794,0.0005376068,0.001602299,0.0009629366,0.000161062,0.00007432038,0.0003349001,0.0002291851,0.000007836883],"category_scores_gemma":[0.0005236414,0.0003997297,0.001547218,0.0008849334,0.0005653078,0.0001942908,0.0001188686,0.0009530261,0.000001596837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004312994,"about_ca_system_score_gemma":0.0003064776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001169926,"about_ca_topic_score_gemma":1.96036e-7,"domain_scores_codex":[0.995622,0.0005031491,0.0008640425,0.0007471755,0.001669345,0.0005942917],"domain_scores_gemma":[0.9969273,0.001352522,0.0003788581,0.0009198358,0.0003632345,0.00005829767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003308328,0.00005347347,0.9760514,0.003560999,0.001117501,0.0003595531,0.0068744,0.0007514655,0.0000908661,0.0001211396,0.002597744,0.008388347],"study_design_scores_gemma":[0.01064274,0.00006293929,0.8609583,0.01868727,0.007025422,0.003327175,0.01357953,0.07155561,0.0002237796,0.0006480382,0.01077162,0.002517617],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3108705,0.0443727,0.5308564,0.1075401,0.00104226,0.003604705,0.00008777099,0.0002410244,0.001384549],"genre_scores_gemma":[0.9847317,0.0005266489,0.001170426,0.01224267,0.0008813355,0.00007494049,0.0002806148,0.00008626118,0.000005430867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6738611,"threshold_uncertainty_score":0.9998454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04507285714669774,"score_gpt":0.2530240905937699,"score_spread":0.2079512334470722,"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."}}