{"id":"W2801550820","doi":"10.1016/j.compbiomed.2018.05.001","title":"Estimation and tracking of AP-diameter of the inferior vena cava in ultrasound images using a novel active circle algorithm","year":2018,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Inferior vena cava; Algorithm; Context (archaeology); Computer science; Ellipsoid; Segmentation; Ultrasound; Artificial intelligence; Tracking (education); Computer vision; Medicine; Radiology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002336885,0.00006685616,0.0002638382,0.000112364,0.00002266203,9.778048e-7,0.00003732395,0.00007384412,0.000002064285],"category_scores_gemma":[0.0001148449,0.00004599908,0.00001256004,0.0001237512,0.0006156517,0.00002516232,0.00002104257,0.000111403,3.658803e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002286727,"about_ca_system_score_gemma":0.00002588196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002332584,"about_ca_topic_score_gemma":0.000008778488,"domain_scores_codex":[0.9994978,0.00004146184,0.0001958347,0.0001265515,0.00004209591,0.00009620711],"domain_scores_gemma":[0.9995291,0.0002282114,0.00008268212,0.00009817695,0.00003674193,0.00002506768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001154846,0.00008672813,0.1479967,0.00009495307,0.00004670181,0.000002479102,0.004501164,0.000008763171,0.337994,0.00007467682,0.000003417048,0.5090749],"study_design_scores_gemma":[0.003382947,0.0006290905,0.9486775,0.001366238,0.00003532031,0.0001143856,0.0002349879,0.0219482,0.0224992,0.00102015,0.00001882388,0.00007315116],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9399072,0.0002791992,0.05915104,0.0001901617,0.0002992771,0.0001346595,0.000003345875,0.000003814966,0.00003131547],"genre_scores_gemma":[0.9816731,0.00007371263,0.01803394,0.00009269739,0.0001164467,0.000001379712,0.000002748063,0.000004226218,0.000001742419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8006808,"threshold_uncertainty_score":0.2268395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326717362733625,"score_gpt":0.344973798007236,"score_spread":0.3217066243798997,"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."}}