{"id":"W4367848714","doi":"10.1148/ryai.230001","title":"Augmentation of the RSNA Pulmonary Embolism CT Dataset with Bounding Box Annotations and Anatomic Localization of Pulmonary Emboli","year":2023,"lang":"en","type":"article","venue":"Radiology Artificial Intelligence","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Pulmonary embolism; Nuclear medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001276903,0.003199374,0.001683801,0.003522982,0.0008981426,0.002247403,0.00220524,0.002624154,0.007466422],"category_scores_gemma":[0.00535955,0.0007770017,0.002286219,0.002206972,0.0006086352,0.001076385,0.001900858,0.001786436,0.01024835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009014622,"about_ca_system_score_gemma":0.001964941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03096498,"about_ca_topic_score_gemma":0.06029198,"domain_scores_codex":[0.9988451,0.0001541273,0.00008903112,0.0004365894,0.0003361583,0.0001388982],"domain_scores_gemma":[0.9980819,0.0006725667,0.0001007352,0.0004875543,0.0004949993,0.0001621772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002348839,0.001315157,0.02665807,0.003090279,0.0009565069,0.002330376,0.0002581099,0.02646205,0.01809872,0.001216753,0.6421553,0.2751098],"study_design_scores_gemma":[0.001294751,0.001293392,0.08547807,0.001629953,0.001369045,0.01353302,0.0008153175,0.3056805,0.03895721,0.007145289,0.5423456,0.0004577378],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1403768,0.01162053,0.03275494,0.002239225,0.001704972,0.0009166091,0.759288,0.03672615,0.01437286],"genre_scores_gemma":[0.07661376,0.001428021,0.03345706,0.0004921681,0.0002145477,0.0003705011,0.8830975,0.0007530964,0.003573408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03096498,"threshold_uncertainty_score":0.06156945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03354814680634203,"score_gpt":0.3103254225538253,"score_spread":0.2767772757474833,"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."}}