{"id":"W2340609529","doi":"10.1097/mcp.0b013e32821acdbe","title":"Multidetector computed tomography for the diagnosis of acute pulmonary embolism","year":2007,"lang":"en","type":"review","venue":"Current Opinion in Pulmonary Medicine","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Pulmonary embolism; Radiology; Venography; Pulmonary angiography; Angiography; Predictive value of tests; D-dimer; Pre- and post-test probability; Computed tomography angiography; Multislice computed tomography; Spiral computed tomography; Positive predicative value; Predictive value; Helical computed tomography; Thrombosis; Computed tomography; Cardiology; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001417531,0.0009993671,0.004928758,0.001719133,0.0001549428,0.00001271046,0.0007934363,0.0004452557,0.000170458],"category_scores_gemma":[0.0001847038,0.0006187198,0.00133191,0.001919383,0.0005407184,0.00008826589,0.0003161744,0.000969122,0.00001479523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001967244,"about_ca_system_score_gemma":0.000211009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009315315,"about_ca_topic_score_gemma":0.000002118858,"domain_scores_codex":[0.9945562,0.0001910163,0.002450425,0.001036416,0.0009248611,0.0008410661],"domain_scores_gemma":[0.9949044,0.002172734,0.001077861,0.001245104,0.0002769142,0.0003229697],"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":[0.0000982182,0.001588148,0.0003261908,0.06429735,0.001032238,0.0000377237,0.00009667425,0.000001766235,5.757902e-7,0.0003660761,0.01602889,0.9161261],"study_design_scores_gemma":[0.001144151,0.0005071252,0.003753432,0.09129464,0.004459806,0.0001227714,0.00007410355,0.000261806,0.00000136844,0.00005704008,0.8978577,0.0004661176],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000897448,0.9770993,0.0005093521,0.0007364904,0.01295987,0.008052554,0.0002859668,0.00009402239,0.0002534506],"genre_scores_gemma":[0.0001612084,0.9907502,0.0001791854,0.000100047,0.003696886,0.003038913,0.001863344,0.0001516037,0.00005862852],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.91566,"threshold_uncertainty_score":0.9996264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1405567988876559,"score_gpt":0.4244653564291749,"score_spread":0.283908557541519,"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."}}