{"id":"W2011082917","doi":"10.1016/s1053-8119(02)00017-4","title":"Deformation-based surface morphometry applied to gray matter deformation","year":2003,"lang":"en","type":"article","venue":"NeuroImage","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":277,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Flattening; Gaussian curvature; Smoothing; Brain morphometry; Curvature; Surface (topology); Surface reconstruction; Geometry; Mean curvature; Mathematics; Artificial intelligence; Physics; Computer vision; Geology; Computer science; Magnetic resonance imaging","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004205907,0.0001592321,0.0001399098,0.0002018271,0.0001110676,0.0002310756,0.0005360157,0.00004879358,0.0002915763],"category_scores_gemma":[0.0001138585,0.0001473895,0.00004538148,0.0007694496,0.00003229102,0.0007377086,0.00007140353,0.0001523696,0.00193485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006131671,"about_ca_system_score_gemma":0.00005166279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007132929,"about_ca_topic_score_gemma":6.456053e-7,"domain_scores_codex":[0.9984628,0.000110524,0.0003390536,0.0003135601,0.0004838614,0.0002901877],"domain_scores_gemma":[0.9989253,0.00009524844,0.000107286,0.0006042229,0.00008071095,0.0001872107],"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":[0.00004461803,0.0006932786,0.01018207,0.0003901223,0.00003071527,0.00007536318,0.002653321,0.005502859,0.6740378,0.01817875,0.2103915,0.07781956],"study_design_scores_gemma":[0.0006433513,0.00008978445,0.00948307,0.00001814251,0.000006581269,0.00002179961,0.00003523443,0.01185369,0.9721919,0.0007624708,0.004462619,0.0004313769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02796768,0.000004369979,0.9595014,0.0006406895,0.0001802324,0.0004068575,0.000002522101,0.0004037013,0.01089249],"genre_scores_gemma":[0.6073856,9.72587e-7,0.3781437,0.01425674,0.0000110031,0.00003588971,0.00001101,0.0000150958,0.000140035],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5813578,"threshold_uncertainty_score":0.9988422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01311589301068927,"score_gpt":0.2521528256665235,"score_spread":0.2390369326558343,"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."}}