{"id":"W1943028203","doi":"10.1515/itit-2015-0011","title":"Model-based analysis of cerebrovascular diseases combining 3D and 4D MRA datasets","year":2015,"lang":"en","type":"article","venue":"it - Information Technology","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Stroke (engine); Segmentation; Computer science; Cerebral blood flow; Blood flow; High resolution; Medicine; Artificial intelligence; Radiology; Cardiology","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":[0.001557573,0.001057439,0.001094116,0.004806779,0.0004313633,0.002303836,0.0007624192,0.001378006,0.001317931],"category_scores_gemma":[0.002271462,0.0004996722,0.002432825,0.002053467,0.0003522953,0.0005708712,0.0008592047,0.0006291512,0.0006562008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000738997,"about_ca_system_score_gemma":0.0009193688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01579059,"about_ca_topic_score_gemma":0.0119145,"domain_scores_codex":[0.9994203,0.0001723549,0.00006288709,0.0001608926,0.0001246438,0.00005902031],"domain_scores_gemma":[0.9993547,0.000244916,0.00007397463,0.0001317752,0.0001518889,0.00004282671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007417967,0.0004493307,0.024429,0.0002972667,0.001121052,0.0006498115,0.0001102955,0.7608027,0.01825324,0.00141547,0.005468516,0.1862616],"study_design_scores_gemma":[0.00001012377,0.0000429418,0.004973843,0.00001338187,0.00006322324,0.0001075546,0.00002458564,0.9913072,0.00207457,0.0006873888,0.000675759,0.00001945613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5521826,0.002999952,0.4259568,0.001201456,0.000354591,0.0003637354,0.008687754,0.005562869,0.002690353],"genre_scores_gemma":[0.8831656,0.0008964861,0.1067674,0.0001196551,0.00009248365,0.0001888452,0.007451556,0.0001419772,0.001176021],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01579059,"threshold_uncertainty_score":0.03139734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01972760063449033,"score_gpt":0.283388406725437,"score_spread":0.2636608060909467,"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."}}