{"id":"W1984690585","doi":"10.1002/jmri.23612","title":"A novel MRI‐compatible brain ventricle phantom for validation of segmentation and volumetry methods","year":2012,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging","keywords":"Imaging phantom; Ventricle; Segmentation; Nuclear medicine; Magnetic resonance imaging; Medicine; Cerebral ventricle; Biomedical engineering; Voxel; Computer science; Radiology; Artificial intelligence; Anatomy; 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":[],"consensus_categories":[],"category_scores_codex":[0.002305568,0.00009157177,0.0002073666,0.0002294184,0.00004923542,0.0000727758,0.0002796444,0.00002290304,0.00002072087],"category_scores_gemma":[0.0004900343,0.00008413864,0.00006126131,0.0003130774,0.00006045659,0.001264468,0.00007007648,0.00009497045,4.860393e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000448017,"about_ca_system_score_gemma":0.00004699381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000890511,"about_ca_topic_score_gemma":1.013561e-7,"domain_scores_codex":[0.9986298,0.0001342016,0.0005596257,0.000121765,0.0003498786,0.0002046969],"domain_scores_gemma":[0.998451,0.0004817546,0.0005598961,0.0001460069,0.0002503748,0.0001109757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001248621,0.0000838151,0.005369643,0.00003969827,0.000003726647,8.445477e-7,0.0006574867,0.000003736432,0.2149179,0.0001410695,0.001350335,0.7774193],"study_design_scores_gemma":[0.001976075,0.0003223288,0.02730928,0.0001792635,0.00003850713,0.0002014983,0.0002339643,0.04587151,0.9195651,0.001156791,0.00296924,0.0001764534],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01258289,0.008232008,0.9778584,0.0008331166,0.0002346309,0.0002053563,0.000002238833,0.0000176924,0.00003363775],"genre_scores_gemma":[0.05211019,0.00009887413,0.9473451,0.0002921147,0.00009392134,0.000008780001,8.615606e-7,0.000008091915,0.00004202357],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7772428,"threshold_uncertainty_score":0.3431074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02448720903494261,"score_gpt":0.3618050737261155,"score_spread":0.3373178646911729,"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."}}