{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002135066,0.0008011952,0.0004367984,0.0006871665,0.0003917614,0.0006027673,0.001099498,0.0009857161,0.001937887],"category_scores_gemma":[0.003262894,0.0004060475,0.0004327245,0.0003455512,0.0007152829,0.0005402219,0.0006620355,0.0005240616,0.0005773451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004617025,"about_ca_system_score_gemma":0.001118997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004326113,"about_ca_topic_score_gemma":0.0004993891,"domain_scores_codex":[0.9992329,0.0001814185,0.00006462862,0.00013736,0.0003439056,0.00003975591],"domain_scores_gemma":[0.9984183,0.0006516721,0.0002076384,0.0003446626,0.0002821519,0.00009549531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002836831,0.0002481034,0.001322228,0.0003281717,0.00002947218,0.0003684752,0.0002481046,0.007766309,0.960602,0.002090808,0.0009539371,0.02575872],"study_design_scores_gemma":[0.0002268305,0.001728422,0.005768982,0.0001130791,0.000104721,0.004256378,0.00009578102,0.05860814,0.902423,0.001267162,0.02529505,0.0001124384],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1278482,0.000771909,0.8656321,0.0002969241,0.000197783,0.0007951898,0.0006228438,0.001935615,0.00189952],"genre_scores_gemma":[0.2828777,0.0006648384,0.7102826,0.0001857742,0.00004942655,0.002024778,0.001230775,0.0006015274,0.002082639],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002135066,"threshold_uncertainty_score":0.01129144,"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."}}