{"id":"W327862399","doi":"10.1007/978-3-319-03590-1","title":"Bio-Imaging and Visualization for Patient-Customized Simulations","year":2013,"lang":"en","type":"book","venue":"Lecture notes in computational vision and biomechanics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Visualization; Computer science; Data science; Computer graphics (images); Medical physics; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001765683,0.0002665986,0.0004291139,0.0004993891,0.0001363636,0.00008958278,0.00004554679,0.0002430148,0.00004512593],"category_scores_gemma":[0.0004903695,0.0002199,0.0000717346,0.0001513166,0.00007431977,0.0000627004,0.00007020816,0.0003245185,0.000002691341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009750465,"about_ca_system_score_gemma":0.0001490052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007225478,"about_ca_topic_score_gemma":0.000001850929,"domain_scores_codex":[0.9987041,0.0000395481,0.0004059414,0.000377155,0.0002863951,0.0001868616],"domain_scores_gemma":[0.9984466,0.000929062,0.0001893803,0.0001024055,0.0002058261,0.0001267115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002105234,0.0001335944,0.0001574489,0.0006646348,0.00009592639,0.00001293205,0.0005032076,0.008644861,0.001560555,0.007647056,0.003148004,0.9772213],"study_design_scores_gemma":[0.001976195,0.0001626089,0.00004837421,0.0004630962,0.00007518873,0.00004187921,0.000005862179,0.8870593,0.00003795137,0.09245526,0.01746072,0.0002135639],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003519977,0.00176473,0.9883192,0.004254728,0.0003621535,0.001312897,0.00006759205,0.0000778722,0.0003208646],"genre_scores_gemma":[0.8883708,0.0004583691,0.09194683,0.009498286,0.0006566254,0.00005746929,0.0062191,0.0002101542,0.002582357],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9770077,"threshold_uncertainty_score":0.8967264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008786600565870092,"score_gpt":0.3045838399610278,"score_spread":0.2957972393951577,"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."}}